Computational modelling folate metabolism and DNA methylation: implications for understanding health and ageing.

Dietary folates have a key role to play in health, as deficiencies in the intake of these B vitamins have been implicated in a wide variety of clinical conditions. The reason for this is folates function as single carbon donors in the synthesis of methionine and nucleotides. Moreover, folates have a vital role to play in the epigenetics of mammalian cells by supplying methyl groups for DNA methylation reactions. Intriguingly, a growing body of experimental evidence suggests that DNA methylation status could be a central modulator of the ageing process. This has important health implications because the methylation status of the human genome could be used to infer age-related disease risk. Thus, it is imperative we further our understanding of the processes which underpin DNA methylation and how these intersect with folate metabolism and ageing. The biochemical and molecular mechanisms, which underpin these processes, are complex. However, computational modelling offers an ideal framework for handling this complexity. A number of computational models have been assembled over the years, but to date, no model has represented the full scope of the interaction between the folate cycle and the reactions, which governs the DNA methylation cycle. In this review, we will discuss several of the models, which have been developed to represent these systems. In addition, we will present a rationale for developing a combined model of folate metabolism and the DNA methylation cycle.

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.

Modelling the molecular mechanisms of aging.

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field.

Aging and computational systems biology.

Aging research is undergoing a paradigm shift, which has led to new and innovative methods of exploring this complex phenomenon. The systems biology approach endeavors to understand biological systems in a holistic manner, by taking account of intrinsic interactions, while also attempting to account for the impact of external inputs, such as diet. A key technique employed in systems biology is computational modeling, which involves mathematically describing and simulating the dynamics of biological systems. Although a large number of computational models have been developed in recent years, these models have focused on various discrete components of the aging process, and to date no model has succeeded in completely representing the full scope of aging. Combining existing models or developing new models may help to address this need and in so doing could help achieve an improved understanding of the intrinsic mechanisms which underpin aging.

Mathematical modelling of metabolic regulation in aging.

The underlying cellular mechanisms that characterize aging are complex and multifaceted. However, it is emerging that aging could be regulated by two distinct metabolic hubs. These hubs are the pathway defined by the mammalian target of rapamycin (mTOR) and that defined by the NAD+-dependent deacetylase enzyme, SIRT1. Recent experimental evidence suggests that there is crosstalk between these two important pathways; however, the mechanisms underpinning their interaction(s) remains poorly understood. In this review, we propose using computational modelling in tandem with experimentation to delineate the mechanism(s). We briefly discuss the main modelling frameworks that could be used to disentangle this relationship and present a reduced reaction pathway that could be modelled. We conclude by outlining the limitations of computational modelling and by discussing opportunities for future progress in this area.

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.

Computational systems biology for aging research.

Computational modelling is a key component of systems biology and integrates with the other techniques discussed thus far in this book by utilizing a myriad of data that are being generated to quantitatively represent and simulate biological systems. This chapter will describe what computational modelling involves; the rationale for using it, and the appropriateness of modelling for investigating the aging process. How a model is assembled and the different theoretical frameworks that can be used to build a model are also discussed. In addition, the chapter will describe several models which demonstrate the effectiveness of each computational approach for investigating the constituents of a healthy aging trajectory. Specifically, a number of models will be showcased which focus on the complex age-related disorders associated with unhealthy aging. To conclude, we discuss the future applications of computational systems modelling to aging research.

Lipid metabolism and hormonal interactions: impact on cardiovascular disease and healthy aging.

Populations in developed nations are aging gradually; it is predicted that by 2050 almost a quarter of the world's population will be over 60 years old, more than twice the figure at the turn of the 20th century. Although we are living longer, this does not mean the extra years will be spent in good health. Cardiovascular diseases are the primary cause of ill health and their prevalence increases with age. Traditionally, lipid biomarkers have been utilized to stratify disease risk and predict the onset of cardiovascular events. However, recent evidence suggests that hormonal interplay with lipid metabolism could have a significant role to play in modulating cardiovascular disease risk. This review will explore recent findings which have investigated the role hormones have on the dynamics of lipid metabolism. The aim is to offer an insight into potential avenues for therapeutic intervention.

Folate and vitamin B12: friendly or enemy nutrients for the elderly.

In the UK vitamin B12 deficiency occurs in approximately 20% of adults aged >65 years. This incidence is significantly higher than that among the general population. The reported incidence invariably depends on the criteria of deficiency used, and in fact estimates rise to 24% and 46% among free-living and institutionalised elderly respectively when methylmalonic acid is used as a marker of vitamin B12 status. The incidence of, and the criteria for diagnosis of, deficiency have drawn much attention recently in the wake of the implementation of folic acid fortification of flour in the USA. This fortification strategy has proved to be extremely successful in increasing folic acid intakes pre-conceptually and thereby reducing the incidence of neural-tube defects among babies born in the USA since 1998. However, in successfully delivering additional folic acid to pregnant women fortification also increases the consumption of folic acid of everyone who consumes products containing flour, including the elderly. It is argued that consuming additional folic acid (as 'synthetic' pteroylglutamic acid) from fortified foods increases the risk of 'masking' megaloblastic anaemia caused by vitamin B12 deficiency. Thus, a number of issues arise for discussion. Are clinicians forced to rely on megaloblastic anaemia as the only sign of possible vitamin B12 deficiency? Is serum vitamin B12 alone adequate to confirm vitamin B12 deficiency or should other diagnostic markers be used routinely in clinical practice? Is the level of intake of folic acid among the elderly (post-fortification) likely to be so high as to cure or 'mask' the anaemia associated with vitamin B12 deficiency?