A whole-body mathematical model of cholesterol metabolism and its age-associated dysregulation

"Add-on" effect of phytosterols-enriched fermented milk on lipids and markers of cholesterol metabolism in statin-treated elderly patients

The effect of plant sterol (PS) enriched matrices on lipid profile has been evaluated in statin-treated individuals, with LDL-C concentrations between 3.35mmol/L and 4.90mmol/L, but studies in the elderly are scarce. In this study the additional effect of a low-fat PS-enriched fermented milk (PS-FM) on cholesterol metabolism markers and serum lipids was evaluated in the elderly on stable statin therapy with baseline LDL-C<3.35mmol/L. Thirty-five individuals (88.6% women; 81±8years old; BMI 29.9±6.0kg/m(2)), living in elderly nursing care facilities were placed on a daily intake of 2g PS-FM for 6weeks, in addition to their statin monotherapy. A fasting blood sample was collected at baseline (t0), after 2 consecutive periods of 3weeks intake (t1 and t2), and after 6weeks of washout (t3), for the analysis of serum lipid profile and cholesterol synthesis (lathosterol, desmosterol) and absorption (sitosterol, campesterol and cholestanol) markers. PS-FM consumption led to a LDL-C reduction of 0.15mmol/L (t1) and 0.27mmol/L (t2) from baseline (P<0.05). Serum campesterol and sitosterol (P<0.001) increased (t0-t1; t0-t2), reflecting PS intake and contributing to the inhibition of cholesterol intestinal absorption, leading to a decrease in cholestanol-to-cholesterol ratio. There was a reciprocal homeostatic rise of serum cholesterol precursors, desmosterol and lathosterol (P<0.001) from baseline, based on the up-regulation of the opposing pathway. Statin-treated elderly individuals, with baseline LDL-C<3.35mmol/L, may still have therapeutic benefit from strategies that reduce cholesterol absorption, such as 2g/day PS-FM.

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.

Ethnic differences in the association between lipid metabolism genes and lipid levels in black and white South African women

OBJECTIVE

Dyslipidaemia can lead to the development of atherosclerosis and cardiovascular disease (CVD), however its prevalence has been shown to differ between ethnic groups in South Africa (SA). Therefore the aim of this study was to investigate ethnic differences in the association between serum lipid levels and polymorphisms within genes involved in lipid metabolism in black and white SA women.

METHODS

In a convenient sample of 234 white and 209 black SA women of Xhosa ancestry, body composition (DXA) and fasting serum lipids were measured. Participants were genotyped for the cholesteryl ester transfer protein (CETP, rs708272, B1/B2), lipoprotein lipase (LPL, rs328, S/X), hepatic lipase (LIPC, rs1800588, C/T) and proprotein convertase subtilisin/kexin type 9 (PCSK9, rs28362286, C/X) polymorphisms.

RESULTS

Compared to white women, black women had lower concentrations of serum total cholesterol (TC, P < 0.001), low density lipoprotein cholesterol (LDL-C, P < 0.001), high density lipoprotein cholesterol (HDL-C, P < 0.001) and triglycerides (TG, P < 0.001). There were significant differences in the genotype and allele frequency distributions between black and white women for the LPL S/X (P < 0.001), PCSK9 C679X (P = 0.002) and LIPC 514C/T (P < 0.001) polymorphisms. In black women only, there were genotype effects on serum lipid levels. Specifically, women with the LPL SX genotype had lower TC and LDL-C and higher HDL-C concentrations than those with the SS genotype and women with the CETP B2 allele had lower LDL-C concentrations than those with the B1B1 genotype.

CONCLUSION

Polymorphisms within the LPL and CETP genes were associated with a more protective lipid profile in black, but not white SA women. This supports the hypothesis that the more favorable lipid profile of black compared to white SA women is associated with polymorphisms in lipid metabolism genes, specifically the LPL and CETP genes.

Systems Biology and Synthetic Biology: A New Epoch for Toxicology Research

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.

A Mechanistic Systems Pharmacology Model for Prediction of LDL Cholesterol Lowering by PCSK9 Antagonism in Human Dyslipidemic Populations

PCSK9 is a promising target for the treatment of hyperlipidemia and cardiovascular disease. A Quantitative Systems Pharmacology model of the mechanisms of action of statin and anti-PCSK9 therapies was developed to predict low density lipoprotein (LDL) changes in response to anti-PCSK9 mAb for different treatment protocols and patient subpopulations. Mechanistic interactions and cross-regulation of LDL, LDL receptor, and PCSK9 were modeled, and numerous virtual subjects were developed and validated against clinical data. Simulations predict a slightly greater maximum percent reduction in LDL cholesterol (LDLc) when anti-PCSK9 is administered on statin background therapy compared to as a monotherapy. The difference results primarily from higher PCSK9 levels in patients on statin background. However, higher PCSK9 levels are also predicted to increase clearance of anti-PCSK9, resulting in a faster rebound of LDLc. Simulations of subjects with impaired LDL receptor (LDLR) function predict compromised anti-PCSK9 responses in patients such as homozygous familial hypercholesterolemics, whose functional LDLR is below 10% of normal.

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.

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.

An in-silico model of lipoprotein metabolism and kinetics for the evaluation of targets and biomarkers in the reverse cholesterol transport pathway

High-density lipoprotein (HDL) is believed to play an important role in lowering cardiovascular disease (CVD) risk by mediating the process of reverse cholesterol transport (RCT). Via RCT, excess cholesterol from peripheral tissues is carried back to the liver and hence should lead to the reduction of atherosclerotic plaques. The recent failures of HDL-cholesterol (HDL-C) raising therapies have initiated a re-examination of the link between CVD risk and the rate of RCT, and have brought into question whether all target modulations that raise HDL-C would be atheroprotective. To help address these issues, a novel in-silico model has been built to incorporate modern concepts of HDL biology, including: the geometric structure of HDL linking the core radius with the number of ApoA-I molecules on it, and the regeneration of lipid-poor ApoA-I from spherical HDL due to remodeling processes. The ODE model has been calibrated using data from the literature and validated by simulating additional experiments not used in the calibration. Using a virtual population, we show that the model provides possible explanations for a number of well-known relationships in cholesterol metabolism, including the epidemiological relationship between HDL-C and CVD risk and the correlations between some HDL-related lipoprotein markers. In particular, the model has been used to explore two HDL-C raising target modulations, Cholesteryl Ester Transfer Protein (CETP) inhibition and ATP-binding cassette transporter member 1 (ABCA1) up-regulation. It predicts that while CETP inhibition would not result in an increased RCT rate, ABCA1 up-regulation should increase both HDL-C and RCT rate. Furthermore, the model predicts the two target modulations result in distinct changes in the lipoprotein measures. Finally, the model also allows for an evaluation of two candidate biomarkers for in-vivo whole-body ABCA1 activity: the absolute concentration and the % lipid-poor ApoA-I. These findings illustrate the potential utility of the model in drug development.

Control of cholesterol homeostasis by entero-hepatic bile transport – the role of feedback mechanisms

Cholesterol homeostasis is achieved through a tight regulation between synthesis, dietary absorption, utilization of bile salts, and excretion in the entero-hepatic compartment.