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

Association between perioperative blood transfusion and length of hospital stay in patients with osteoporotic fractures

BACKGROUND

Few studies have examined the relationship between perioperative blood transfusion (PBT) and length of hospital stay (LOS) in patients with osteoporotic fractures. This research aims to study the association between PBT and LOS.

METHODS

This is a retrospective cross-sectional study from the Affiliated Kunshan Hospital of Jiangsu University, Suzhou, China, involving 2357 osteoporotic fractures (OPF) patients who received surgical treatment during hospitalization from January 2017 and March 2022. Multiple linear regression was used to analyze the relationship between PBT and LOS. In the analysis, PBT volume was the dependent variable, whereas LOS was the independent variable. Simultaneously, age, gender, body mass index, hemoglobin, primary diagnosis, American Society of Anesthesiologists, creatinine (Cr), anesthesia, surgical method, and Charlson comorbidity index were included as covariates. The generalized additive model was then used to study nonlinear associations. Two piecewise linear regression exemplary evaluated the inception results for smoothing the curve.

RESULTS

Our results proved that PBT was positively correlated with LOS in the fully adjusted model (β, 0.21; 95% CI, 0.04 to 0.37; P < 0.0001). Furthermore, a "U-shape" nonlinear relationship existed between PBT and LOS. When the concentration of PBT was between 0 and 1.5 units, it was manifested as a negative correlation between PBT and LOS. However, there was a positive association between PBT and LOS when PBT levels exceeded 1.5 units.

CONCLUSIONS

This study demonstrated that PBT and LOS in the OPF population were independent with a nonlinear relationship. These results suggest that PBT may be protective for patients with long LOS. If these findings are confirmed, the LOS in OPF patients can be regulated through appropriate perioperative blood transfusion.

Mathematical models of cystic fibrosis as a systemic disease

Cystic fibrosis (CF) is widely known as a disease of the lung, even though it is in truth a systemic disease, whose symptoms typically manifest in gastrointestinal dysfunction first. CF ultimately impairs not only the pancreas and intestine but also the lungs, gonads, liver, kidneys, bones, and the cardiovascular system. It is caused by one of several mutations in the gene of the epithelial ion channel protein CFTR. Intense research and improved antimicrobial treatments during the past eight decades have steadily increased the predicted life expectancy of a person with CF (pwCF) from a few weeks to over 50 years. Moreover, several drugs ameliorating the sequelae of the disease have become available in recent years, and notable treatments of the root cause of the disease have recently generated substantial improvements in health for some but not all pwCF. Yet, numerous fundamental questions remain unanswered. Complicating CF, for instance in the lung, is the fact that the associated insufficient chloride secretion typically perturbs the electrochemical balance across epithelia and, in the airways, leads to the accumulation of thick, viscous mucus and mucus plaques that cannot be cleared effectively and provide a rich breeding ground for a spectrum of bacterial and fungal communities. The subsequent infections often become chronic and respond poorly to antibiotic treatments, with outcomes sometimes only weakly correlated with the drug susceptibility of the target pathogen. Furthermore, in contrast to rapidly resolved acute infections with a single target pathogen, chronic infections commonly involve multi-species bacterial communities, called "infection microbiomes," that develop their own ecological and evolutionary dynamics. It is presently impossible to devise mathematical models of CF in its entirety, but it is feasible to design models for many of the distinct drivers of the disease. Building upon these growing yet isolated modeling efforts, we discuss in the following the feasibility of a multi-scale modeling framework, known as template-and-anchor modeling, that allows the gradual integration of refined sub-models with different granularity. The article first reviews the most important biomedical aspects of CF and subsequently describes mathematical modeling approaches that already exist or have the potential to deepen our understanding of the multitude aspects of the disease and their interrelationships. The conceptual ideas behind the approaches proposed here do not only pertain to CF but are translatable to other systemic diseases. This article is categorized under: Congenital Diseases > Computational Models.

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.

Association of 25-hydroxyvitamin D levels with lipid profiles in osteoporosis patients: a retrospective cross-sectional study

BACKGROUND

In the literature, scarce data investigate the link between 25-hydroxyvitamin D (25[OH]D) and blood lipids in the osteoporosis (OP) population. 25(OH)D, as a calcium-regulating hormone, can inhibit the rise of parathyroid hormone, increase bone mineralization to prevent bone loss, enhance muscle strength, improve balance, and prevent falls in the elderly. This retrospective cross-sectional study aimed to investigate the association between serum 25(OH)D levels and lipid profiles in patients with osteoporosis, with the objective of providing insight for appropriate vitamin D supplementation in clinical settings to potentially reduce the incidence of cardiovascular disease, which is known to be a major health concern for individuals with osteoporosis.

METHODS

This is a retrospective cross-sectional study from the Affiliated Kunshan Hospital of Jiangsu University, including 2063 OP patients who received biochemical blood analysis of lipids during hospitalization from January 2015 to March 2022. The associations between serum lipids and 25(OH)D levels were examined by multiple linear regression. The dependent variables in the analysis were the concentrations of serum lipoprotein, total cholesterol (TC), triglycerides (TGs), apolipoprotein-A, lipoprotein A, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (LDL-C). The independent variable was the concentration of blood serum 25(OH)D. At the same time, age, body mass index, sex, time and year of serum analysis, primary diagnosis, hypertension, diabetes, statins usage, beta-C-terminal telopeptide of type I collagen, procollagen type I N-terminal propeptide were covariates. Blood samples were collected in the early morning after the overnight fasting and were analyzed using an automated electrochemiluminescence immunoassay on the LABOSPECT 008AS platform (Hitachi Hi-Tech Co., Ltd., Tokyo, Japan). The generalized additive model was further applied for nonlinear associations. The inception result for smoothing the curve was evaluated by two-piecewise linear regression exemplary.

RESULTS

Our results proved that in the OP patients, the serum 25(OH)D levels were inversely connected with blood TGs concentration, whereas they were positively associated with the HDL, apolipoprotein-A, and lipoprotein A levels. In the meantime, this research also found a nonlinear relationship and threshold effect between serum 25(OH)D and TC, LDL-C. Furthermore, there were positive correlations between the blood serum 25(OH)D levels and the levels of TC and LDL-C when 25(OH)D concentrations ranged from 0 to 10.04 ng/mL. However, this relationship was not present when 25(OH)D levels were higher than 10.04 ng/mL.

CONCLUSIONS

Our results demonstrated an independent relationship between blood lipids and vitamin D levels in osteoporosis patients. While we cannot establish a causal relationship between the two, our findings suggest that vitamin D may have beneficial effects on both bone health and blood lipid levels, providing a reference for improved protection against cardiovascular disease in this population. Further research, particularly interventional studies, is needed to confirm these associations and investigate their underlying mechanisms.

The utility of 3D models to study cholesterol in cancer: Insights and future perspectives

Cholesterol remains a vital molecule required for life; however, increasing evidence exists implicating cholesterol in cancer development and progression. Numerous studies investigating the relationship between cholesterol and cancer in 2-dimensional (2D) culture settings exist, however these models display inherent limitations highlighting the incipient need to develop better models to study disease pathogenesis. Due to the multifaceted role cholesterol plays in the cell, researchers have begun utilizing 3-dimensional (3D) culture systems, namely, spheroids and organoids to recapitulate cellular architecture and function. This review aims to describe current studies exploring the relationship between cancer and cholesterol in a variety of cancer types using 3D culture systems. We briefly discuss cholesterol dyshomeostasis in cancer and introduce 3D in-vitro culture systems. Following this, we discuss studies performed in cancerous spheroid and organoid models that focused on cholesterol, highlighting the dynamic role cholesterol plays in various cancer types. Finally, we attempt to provide potential gaps in research that should be explored in this rapidly evolving field of study.

Systems Biology of Ageing

The ageing process is highly complex involving multiple processes operating at different biological levels. Systems Biology presents an approach using integrative computational and laboratory study that allows us to address such complexity. The approach relies on the computational analysis of knowledge and data to generate predictive models that may be validated with further laboratory experimentation. Our understanding of ageing is such that translational opportunities are within reach and systems biology offers a means to ensure that optimal decisions are made. We present an overview of the methods employed from bioinformatics and computational modelling and describe some of the insights into ageing that have been gained.

Dietary restriction and ageing: Recent evolutionary perspectives

Dietary restriction (DR) represents one of the most robust interventions for extending lifespan. It is not known how DR increases lifespan. The prevailing evolutionary hypothesis suggests the DR response redirects metabolic resources towards somatic maintenance at the expense of investment in reproduction. Consequently, DR acts as a proximate mechanism which promotes a pro-longevity phenotype. This idea is known as resource reallocation. However, growing findings suggest this paradigm could be incomplete. It has been argued that during DR it is not always possible to identify a trade-off between reproduction and lifespan. It is also suggested the relationship between reproduction and somatic maintenance can be uncoupled by the removal or inclusion of specific nutrients. These findings have created an imperative to re-explore the nexus between DR and evolutionary theory. In this review I will address this evolutionary conundrum. My overarching objectives are fourfold: (1) to outline some of the evidence for and against resource reallocation; (2) to examine recent findings which have necessitated a theoretical re-evaluation of the link between life history theory and DR; (3) to present alternatives to the resource reallocation model; (4) to present emerging variables which potentially influence how DR effects evolutionary trade-offs.

Cholesterol-Lowering Effects of Asperidine B, a Pyrrolidine Derivative from the Soil-Derived Fungus Aspergillus sclerotiorum PSU-RSPG178: A Potential Cholesterol Absorption Inhibitor

Isolated secondary metabolites asperidine B (preussin) and asperidine C, produced by the soil-derived fungus Aspergillus sclerotiorum PSU-RSPG178, were found to exhibit inhibitory effects against 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase and oxidative stress in an in vitro assay. Whether or not the known pyrrolidine asperidine B and the recently isolated piperidine asperidine C have lipid-lowering effects remains unknown. Thus, this study aimed to investigate the hypocholesterolemic effects of asperidines B and C and identify the mechanisms involved in using in vitro, ex vivo, and in vivo models. The results show that both compounds interfered with cholesterol micelle formation by increasing bile acid binding capacity, similar to the action of the bile acid sequestrant drug cholestyramine. However, only asperidine B, but not asperidine C, was found to inhibit cholesterol uptake in Caco-2 cells by up-regulating LXRα without changing cholesterol transporter NPC1L1 protein expression. Likewise, reduced cholesterol absorption via asperidine-B-mediated activation of LXRα was also observed in isolated rat jejunal loops. Asperidine B consistently decreases plasma cholesterol absorption, similar to the effect of ezetimibe in rats. Therefore, asperidine B, the pyrrolidine derivative, has therapeutic potential to be developed into a type of cholesterol absorption inhibitor for the treatment of hypercholesterolemia.

A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance

Proportional-Integral-Derivative (PID) feedback controllers are the most widely used controllers in industry. Recently, the design of molecular PID-controllers has been identified as an important goal for synthetic biology and the field of cybergenetics. In this paper, we consider the realization of PID-controllers via biomolecular reactions. We propose an array of topologies offering a compromise between simplicity and high performance. We first demonstrate that different biomolecular PI-controllers exhibit different performance-enhancing capabilities. Next, we introduce several derivative controllers based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop, which can be augmented by PI-components to yield PID-controllers. We demonstrate that PID-controllers can enhance stability and dynamic performance, and can also reduce stochastic noise. Finally, we provide an experimental demonstration using a hybrid setup where in silico PID-controllers regulate a genetic circuit in single yeast cells.

Mathematical Models for Cholesterol Metabolism and Transport

Cholesterol is an essential component of eukaryotic cellular membranes. It is also an important precursor for making other molecules needed by the body. Cholesterol homeostasis plays an essential role in human health. Having high cholesterol can increase the chances of getting heart disease. As a result of the risks associated with high cholesterol, it is imperative that studies are conducted to determine the best course of action to reduce whole body cholesterol levels. Mathematical models can provide direction on this. By examining existing models, the suitable reactions or processes for drug targeting to lower whole-body cholesterol can be determined. This paper examines existing models in the literature that, in total, cover most of the processes involving cholesterol metabolism and transport, including: the absorption of cholesterol in the intestine; the cholesterol biosynthesis in the liver; the storage and transport of cholesterol between the intestine, the liver, blood vessels, and peripheral cells. The findings presented in these models will be discussed for potential combination to form a comprehensive model of cholesterol within the entire body, which is then taken as an in-silico patient for identifying drug targets, screening drugs, and designing intervention strategies to regulate cholesterol levels in the human body.

Modeling cholesterol metabolism and atherosclerosis

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality among Western populations. Many risk factors have been identified for ASCVD; however, elevated low-density lipoprotein cholesterol (LDL-C) remains the gold standard. Cholesterol metabolism at the cellular and whole-body level is maintained by an array of interacting components. These regulatory mechanisms have complex behavior. Likewise, the mechanisms which underpin atherogenesis are nontrivial and multifaceted. To help overcome the challenge of investigating these processes mathematical modeling, which is a core constituent of the systems biology paradigm has played a pivotal role in deciphering their dynamics. In so doing models have revealed new insights about the key drivers of ASCVD. The aim of this review is fourfold; to provide an overview of cholesterol metabolism and atherosclerosis, to briefly introduce mathematical approaches used in this field, to critically discuss models of cholesterol metabolism and atherosclerosis, and to highlight areas where mathematical modeling could help to investigate in the future. This article is categorized under: Cardiovascular Diseases > Computational Models.

Associations between SNPs in Intestinal Cholesterol Absorption and Endogenous Cholesterol Synthesis Genes with Cholesterol Metabolism

Single nucleotide polymorphisms (SNPs) have been associated with cholesterol metabolism and may partly explain large inter-individual variability in intestinal cholesterol absorption and endogenous cholesterol synthesis rates. This cross-sectional study therefore examined whether SNPs in genes encoding for proteins involved in intestinal cholesterol absorption (ABCG5, ABCG8, and NPC1L1) and endogenous cholesterol synthesis (CYP51A1, DHCR7, DHCR24, HMGCR, HSD17B7, LBR, and MSMO1) were associated with intestinal cholesterol absorption markers (total cholesterol (TC) standardized campesterol and sitosterol levels), an endogenous cholesterol synthesis marker (TC-standardized lathosterol levels), and serum low-density lipoprotein cholesterol (LDL-C) concentrations in a European cohort. ABCG5 (rs4245786) and the tag SNP ABCG8 (rs4245791) were significantly associated with serum campesterol and/or sitosterol levels. In contrast, NPC1L1 (rs217429 and rs217416) were significantly associated with serum lathosterol levels. The tag SNP in HMGCR (rs12916) and a SNP in LBR (rs12141732) were significantly associated with serum LDL-C concentrations. SNPs in the cholesterol absorption genes were not associated with serum LDL-C concentrations. SNPs in CYP51A1, DHCR24, HSD17B7, and MSMO1 were not associated with the serum non-cholesterol sterols and LDL-C concentrations. Given the variable efficiency of cholesterol-lowering interventions, the identification of SNPs associated with cholesterol metabolism could be a step forward towards personalized approaches.

The Interdependency and Co-Regulation of the Vitamin D and Cholesterol Metabolism

Vitamin D and cholesterol metabolism overlap significantly in the pathways that contribute to their biosynthesis. However, our understanding of their independent and co-regulation is limited. Cardiovascular disease is the leading cause of death globally and atherosclerosis, the pathology associated with elevated cholesterol, is the leading cause of cardiovascular disease. It is therefore important to understand vitamin D metabolism as a contributory factor. From the literature, we compile evidence of how these systems interact, relating the understanding of the molecular mechanisms involved to the results from observational studies. We also present the first systems biology pathway map of the joint cholesterol and vitamin D metabolisms made available using the Systems Biology Graphical Notation (SBGN) Markup Language (SBGNML). It is shown that the relationship between vitamin D supplementation, total cholesterol, and LDL-C status, and between latitude, vitamin D, and cholesterol status are consistent with our knowledge of molecular mechanisms. We also highlight the results that cannot be explained with our current knowledge of molecular mechanisms: (i) vitamin D supplementation mitigates the side-effects of statin therapy; (ii) statin therapy does not impact upon vitamin D status; and critically (iii) vitamin D supplementation does not improve cardiovascular outcomes, despite improving cardiovascular risk factors. For (iii), we present a hypothesis, based on observations in the literature, that describes how vitamin D regulates the balance between cellular and plasma cholesterol. Answering these questions will create significant opportunities for advancement in our understanding of cardiovascular health.

Intraperitoneal injection of genistein affects the distribution and metabolism of cholesterol in female yellow catfish Tachysurus fulvidraco

Genistein is an abundant phytoestrogen in soybean. This study aimed to determine the effects of genistein on cholesterol distribution and metabolism in female yellow catfish. Three hundred fish (49.2 ± 1.4 g) were randomly divided into five treatments and received intraperitoneal injections as follows: (1) blank, no injection; (2) control, vehicle only; (3) E2, 17β-estradiol at 10 μg·g^-1 body weight; (4) low genistein doses, genistein at 10 μg·g^-1 body weight; (5) high genistein doses, genistein at 100 μg·g^-1 body weight. Both high and low genistein doses significantly reduced (p < 0.05) serum TC and LDL-C 24 h after injection. Moreover, the high genistein doses significantly reduced (p < 0.05) serum HDL-C. Both high and low doses of genistein significantly increased (p < 0.05) hepatic TC. Only high genistein doses significantly increased (p < 0.05) ovary TC. In the liver, both high and low genistein doses significantly increased (p < 0.05) protein and mRNA expression of ldlr. Meanwhile, high genistein doses significantly decreased (p < 0.05) mRNA expression of hmgcr. In ovary tissue, high genistein doses significantly decreased (p < 0.05) mRNA expression of cyp11a1. These results suggested that genistein affected the cholesterol distribution in female yellow catfish. Both high and low doses of genistein reduced cholesterol content in blood and increased its content in the liver by increasing the uptake of blood cholesterol. Meanwhile, high genistein doses may inhibit hepatic cholesterol synthesis. Additionally, high genistein doses could increase cholesterol transfer from serum into the ovary and disturb cholesterol conversion to pregnenolone.

A quantitative systems pharmacology modeling platform for evaluating triglyceride profiles in patients with high triglycerides receiving evinacumab

A model to quantitatively characterize the effect of evinacumab, an investigational monoclonal antibody against angiopoietin‐like protein 3 (ANGPTL3) on lipid trafficking is needed. A quantitative systems pharmacology (QSP) approach was developed to predict the transient responses of different triglyceride (TG)‐rich lipoprotein particles in response to evinacumab administration. A previously published hepatic lipid model was modified to address specific queries relevant to the mechanism of evinacumab and its effect on lipid metabolism. Modifications included the addition of intermediate‐density lipoprotein and low‐density lipoprotein compartments to address the modulation of lipoprotein lipase (LPL) activity by evinacumab, ANGPTL3 biosynthesis and clearance, and a target‐mediated drug disposition model. A sensitivity analysis guided the creation of virtual patients (VPs). The drug‐free QSP model was found to agree well with clinical data published with the initial hepatic liver model over simulations ranging from 20 to 365 days in duration. The QSP model, including the interaction between LPL and ANGPTL3, was validated against clinical data for total evinacumab, total ANGPTL3, and TG concentrations as well as inhibition of apolipoprotein CIII. Free ANGPTL3 concentration and LPL activity were also modeled. In total, seven VPs were created; the lipid levels of the VPs were found to match the range of responses observed in evinacumab clinical trial data. The QSP model results agreed with clinical data for various subjects and was shown to characterize known TG physiology and drug effects in a range of patient populations with varying levels of TGs, enabling hypothesis testing of evinacumab effects on lipid metabolism.

Why is elevation of serum cholesterol associated with exposure to perfluoroalkyl substances (PFAS) in humans? A workshop report on potential mechanisms

Serum concentrations of cholesterol are positively correlated with exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) in humans. The associated change in cholesterol is small across a broad range of exposure to PFOA and PFOS. Animal studies generally have not indicated a mechanism that would account for the association in humans. The extent to which the relationship is causal is an open question. Nonetheless, the association is of particular importance because increased serum cholesterol has been considered as an endpoint to derive a point of departure in at least one recent risk assessment. To gain insight into potential mechanisms for the association, both causal and non-causal, an expert workshop was held Oct 31 and Nov 1, 2019 to discuss relevant data and propose new studies. In this report, we summarize the relevant background data, the discussion among the attendees, and their recommendations for further research.

A robust computational pipeline for model-based and data-driven phenotype clustering

MOTIVATION

Precision medicine is a promising field that proposes, in contrast to a one-size-fits-all approach, the tailoring of medical decisions, treatments or products. In this context, it is crucial to introduce innovative methods to stratify a population of patients on the basis of an accurate system-level knowledge of the disease. This is particularly important in very challenging conditions, where the use of standard statistical methods can be prevented by poor data availability or by the need of oversimplifying the processes regulating a complex disease.

RESULTS

We define an innovative method for phenotype classification that combines experimental data and a mathematical description of the disease biology. The methodology exploits the mathematical model for inferring additional subject features relevant for the classification. Finally, the algorithm identifies the optimal number of clusters and classifies the samples on the basis of a subset of the features estimated during the model fit. We tested the algorithm in two test cases: an in silico case in the context of dyslipidemia, a complex disease for which a large population of patients has been generated, and a clinical test case, in the context of a lysosomal rare disorder, for which the amount of available data was limited. In both the scenarios, our methodology proved to be accurate and robust, and allowed the inference of an additional phenotype division that the experimental data did not show.

AVAILABILITY AND IMPLEMENTATION

The code to reproduce the in silico results has been implemented in MATLAB v.2017b and it is available in the Supplementary Material.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cholesterol Homeostasis: An In Silico Investigation into How Aging Disrupts Its Key Hepatic Regulatory Mechanisms

The dysregulation of intracellular cholesterol homeostasis is associated with several age-related diseases, most notably cardiovascular disease (CVD). Research in this area has benefitted from using computational modelling to study the inherent complexity associated with the regulation of this system. In addition to facilitating hypothesis exploration, the utility of modelling lies in its ability to represent an array of rate limiting enzymatic reactions, together with multiple feedback loops, which collectively define the dynamics of cholesterol homeostasis. However, to date no model has specifically investigated the effects aging has on this system. This work addresses this shortcoming by explicitly focusing on the impact of aging on hepatic intracellular cholesterol homeostasis. The model was used to investigate the experimental findings that reactive oxygen species induce the total activation of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase (HMGCR). Moreover, the model explored the impact of an age-related decrease in hepatic acetyl-CoA acetyltransferase 2 (ACAT2). The model suggested that an increase in the activity of HMGCR does not have as significant an impact on cholesterol homeostasis as a decrease in hepatic ACAT2 activity. According to the model, a decrease in the activity of hepatic ACAT2 raises free cholesterol (FC) and decreases low-density lipoprotein cholesterol (LDL-C) levels. Increased acetyl CoA synthesis resulted in a reduction in the number of hepatic low-density lipoprotein receptors, and increased LDL-C, FC, and cholesterol esters. The rise in LDL-C was restricted by elevated hepatic FC accumulation. Taken together these findings have important implications for healthspan. This is because emerging clinical data suggest hepatic FC accumulation is relevant to the pathogenesis of non-alcoholic fatty liver disease (NAFLD), which is associated with an increased risk of CVD. These pathophysiological changes could, in part, help to explain the phenomenon of increased mortality associated with low levels of LDL-C which have been observed in certain studies involving the oldest old (≥85 years).

An Atomic-Level Perspective of HMG-CoA-Reductase: The Target Enzyme to Treat Hypercholesterolemia

This review provides an updated atomic-level perspective regarding the enzyme 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoAR), linking the more recent data on this enzyme with a structure/function interpretation. This enzyme catalyzes one of the most important steps in cholesterol biosynthesis and is regarded as one of the most important drug targets in the treatment of hypercholesterolemia. Taking this into consideration, we review in the present article several aspects of this enzyme, including its structure and biochemistry, its catalytic mechanism and different reported and proposed approaches for inhibiting this enzyme, including the commercially available statins or the possibility of using dimerization inhibitors.

Exploring the Bacterial Impact on Cholesterol Cycle: A Numerical Study

High blood cholesterol levels are often associated with cardiovascular diseases. Therapeutic strategies, targeting different functions involved in cholesterol transport or synthesis, were developed to control cholesterolemia in human. However, the gut microbiota is also involved in cholesterol regulation by direct biotransformation of luminal cholesterol or conversion of bile salts, opening the way to the design of new strategies to manage cholesterol level. In this report, we developed for the first time a whole-body human model of cholesterol metabolism including the gut microbiota in order to investigate the relative impact of host and microbial pathways. We first used an animal model to investigate the ingested cholesterol distribution in vivo. Then, using in vitro bacterial growth experiments and metabolite measurements, we modeled the population dynamics of bacterial strains in the presence of cholesterol or bile salts, together with their bioconversion function. Next, after correct rescaling to mimic the activity of a complex microbiota, we developed a whole body model of cholesterol metabolism integrating host and microbiota mechanisms. This global model was validated with the animal experiments. Finally, the model was numerically explored to give a further insight into the different flux involved in cholesterol turn-over. According to this model, bacterial pathways appear as an important driver of cholesterol regulation, reinforcing the need for development of novel "bacteria-based" strategies for cholesterol management.

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

The last few decades have witnessed a global rise in the number of older individuals. 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 people's health. It is well established that obesity adversely affects several metabolic systems. However, due to its close association with overall cardiometabolic health, the impact that obesity has on cholesterol metabolism needs to be recognised. The aim of the present review is to critically discuss the effects that obesity has on cholesterol metabolism and to reveal its significance for healthy ageing.

Comparative quantitative systems pharmacology modeling of anti-PCSK9 therapeutic modalities in hypercholesterolemia

Since the discovery of proprotein convertase subtilisin/kexin type 9 (PCSK9) as an attractive target in the treatment of hypercholesterolemia, multiple anti-PCSK9 therapeutic modalities have been pursued in drug development. The objective of this research is to set the stage for the quantitative benchmarking of two anti-PCSK9 pharmacological modality classes, monoclonal antibodies (mAbs) and small interfering RNA (siRNA). To this end, we developed an integrative mathematical model of lipoprotein homeostasis describing the dynamic interplay between PCSK9, LDL-cholesterol (LDL-C), VLDL-cholesterol, HDL-cholesterol (HDL-C), apoB, lipoprotein a [Lp(a)], and triglycerides (TGs). We demonstrate that LDL-C decreased proportionally to PCSK9 reduction for both mAb and siRNA modalities. At marketed doses, however, treatment with mAbs resulted in an additional ∼20% LDL-C reduction compared with siRNA. We further used the model as an evaluation tool and determined that no quantitative differences were observed in HDL-C, Lp(a), TG, or apoB responses, suggesting that the disruption of PCSK9 synthesis would provide no additional effects on lipoprotein-related biomarkers in the patient segment investigated. Predictive model simulations further indicate that siRNA therapies may reach reductions in LDL-C levels comparable to those achieved with mAbs if the current threshold of 80% PCSK9 inhibition via siRNA could be overcome.

In vivo and in silico dynamics of the development of Metabolic Syndrome

The Metabolic Syndrome (MetS) is a complex, multifactorial disorder that develops slowly over time presenting itself with large differences among MetS patients. We applied a systems biology approach to describe and predict the onset and progressive development of MetS, in a study that combined in vivo and in silico models. A new data-driven, physiological model (MINGLeD: Model INtegrating Glucose and Lipid Dynamics) was developed, describing glucose, lipid and cholesterol metabolism. Since classic kinetic models cannot describe slowly progressing disorders, a simulation method (ADAPT) was used to describe longitudinal dynamics and to predict metabolic concentrations and fluxes. This approach yielded a novel model that can describe long-term MetS development and progression. This model was integrated with longitudinal in vivo data that was obtained from male APOE*3-Leiden.CETP mice fed a high-fat, high-cholesterol diet for three months and that developed MetS as reflected by classical symptoms including obesity and glucose intolerance. Two distinct subgroups were identified: those who developed dyslipidemia, and those who did not. The combination of MINGLeD with ADAPT could correctly predict both phenotypes, without making any prior assumptions about changes in kinetic rates or metabolic regulation. Modeling and flux trajectory analysis revealed that differences in liver fluxes and dietary cholesterol absorption could explain this occurrence of the two different phenotypes. In individual mice with dyslipidemia dietary cholesterol absorption and hepatic turnover of metabolites, including lipid fluxes, were higher compared to those without dyslipidemia. Predicted differences were also observed in gene expression data, and consistent with the emergence of insulin resistance and hepatic steatosis, two well-known MetS co-morbidities. Whereas MINGLeD specifically models the metabolic derangements underlying MetS, the simulation method ADAPT is generic and can be applied to other diseases where dynamic modeling and longitudinal data are available.

A seven-year study on an integrated hospital-community diabetes management program in Chinese patients with diabetes

AIMS

To assess whether an integrated hospital-community diabetes management program could improve major cardiovascular risk factor control among patients with diabetes in real-world clinical settings.

METHODS

985 adults with diabetes in the Shanghai Taopu community health service center were enrolled at baseline and 907 subjects completed the follow-up. The follow-up levels of the metabolic profiles were assessed by their averages during the follow up period.

RESULTS

After a mean 7-year follow-up period, heamoglobin A1c, systolic and diastolic blood pressure levels decreased by 0.6%, 5.7mmHg, and 1.5mmHg, respectively (all P<0.001). There was a non-significant difference in low-density lipoprotein cholesterol, while high-density lipoprotein cholesterol increased 1.9mg/dL and triglycerides decreased 28.3mg/dL, respectively (all P<0.001). The percentage of patients with diabetes who met any one of three Chinese Diabetes Society goals (heamoglobin A1c <7.0%, blood pressure <140/80mmHg, and low-density lipoprotein cholesterol <100mg/dL) increased from 58.2% to 70.1%. The chronic diabetes complication screening rates (diabetic retinopathy, diabetic neuropathy, diabetic nephropathy) have significantly increased, from almost zero to 12-78%.

CONCLUSIONS

This long-term program has increased the proportions of attaining major cardiovascular risk factors control goals and diabetic chronic complication screening rates among patients with diabetes.

The role of DNA methylation in ageing and cancer

The aim of the present review paper is to survey the literature related to DNA methylation, and its association with cancer and ageing. The review will outline the key factors, including diet, which modulate DNA methylation. Our rationale for conducting this review is that ageing and diseases, including cancer, are often accompanied by aberrant DNA methylation, a key epigenetic process, which is crucial to the regulation of gene expression. Significantly, it has been observed that with age and certain disease states, DNA methylation status can become disrupted. For instance, a broad array of cancers are associated with promoter-specific hypermethylation and concomitant gene silencing. This review highlights that hypermethylation, and gene silencing, of the EN1 gene promoter, a crucial homeobox gene, has been detected in various forms of cancer. This has led to this region being proposed as a potential biomarker for diseases such as cancer. We conclude the review by describing a recently developed novel electrochemical method that can be used to quantify the level of methylation within the EN1 promoter and emphasise the growing trend in the use of electrochemical techniques for the detection of aberrant DNA methylation.

The Interplay Between Cholesterol Metabolism and Intrinsic Ageing

The last few decades have witnessed remarkable progress in our understanding of ageing. From an evolutionary standpoint it is generally accepted that ageing is a non-adaptive process which is underscored by a decrease in the force of natural selection with time. From a mechanistic perspective ageing is characterized by a wide variety of cellular mechanisms, including processes such as cellular senescence, telomere attrition, oxidative damage, molecular chaperone activity, and the regulation of biochemical pathways by sirtuins. These biological findings have been accompanied by an unrelenting rise in both life expectancy and the number of older people globally. However, despite age being recognized demographically as a risk factor for healthspan, the processes associated with ageing are routinely overlooked in disease mechanisms. Thus, a central goal of biogerontology is to understand how diseases such as cardiovascular disease (CVD) are shaped by ageing. This challenge cannot be ignored because CVD is the main cause of morbidity in older people. A worthwhile way to examine how ageing intersects with CVD is to consider the effects ageing has on cholesterol metabolism, because dysregualted cholesterol metabolism is the key factor which underpins the pathology of CVD. The aim of this chapter is to outline a hypothesis which accounts for how ageing intersects with intracellular cholesterol metabolism. Moreover, we discuss the implications of this relationship for the onset of disease in the 'oldest old' (individuals ≥85 years of age). We conclude the chapter by discussing the important role mathematical modelling has to play in improving our understanding of cholesterol metabolism and ageing.

Linear-In-Flux-Expressions Methodology: Toward a Robust Mathematical Framework for Quantitative Systems Pharmacology Simulators

Quantitative Systems Pharmacology (QSP) modeling is increasingly used as a quantitative tool for advancing mechanistic hypotheses on the mechanism of action of a drug, and its pharmacological effect in relevant disease phenotypes, to enable linking the right drug to the right patient. Application of QSP models relies on creation of virtual populations for simulating scenarios of interest. Creation of virtual populations requires 2 important steps, namely, identification of a subset of model parameters that can be associated with a phenotype of disease and development of a sampling strategy from identified distributions of these parameters. We improve on existing sampling methodologies by providing a means of representing the structural relationship across model parameters and describing propagation of variability in the model. This gives a robust, systematic method for creating a virtual population. We have developed the Linear-In-Flux-Expressions (LIFE) method to simulate variability in patient pharmacokinetics and pharmacodynamics using relationships between parameters at baseline to create a virtual population. We demonstrate the importance of this methodology on a model of cholesterol metabolism. The LIFE methodology brings us a step closer toward improved QSP simulators through enhanced capture of the observed variability in drug and disease clinical data.

Food Ingredients That Inhibit Cholesterol Absorption

Cholesterol is a vital component of the human body. It stabilizes cell membranes and is the precursor of bile acids, vitamin D and steroid hormones. However, cholesterol accumulation in the bloodstream (hypercholesterolemia) can cause atherosclerotic plaques within artery walls, leading to heart attacks and strokes. The efficiency of cholesterol absorption in the small intestine is of great interest because human and animal studies have linked cholesterol absorption with plasma concentration of total and low density lipoprotein cholesterol. Cholesterol absorption is highly regulated and influenced by particular compounds in the food supply. Therefore, it is desirable to learn more about natural food components that inhibit cholesterol absorption so that food ingredients and dietary supplements can be developed for consumers who wish to manage their plasma cholesterol levels by non-pharmacological means. Food components thus far identified as inhibitors of cholesterol absorption include phytosterols, soluble fibers, phospholipids, and stearic acid.

A Quantitative Systems Pharmacology Platform to Investigate the Impact of Alirocumab and Cholesterol-Lowering Therapies on Lipid Profiles and Plaque Characteristics

Reduction in low-density lipoprotein cholesterol (LDL-C) is associated with decreased risk for cardiovascular disease. Alirocumab, an antibody to proprotein convertase subtilisin/kexin type 9 (PCSK9), significantly reduces LDL-C. Here, we report development of a quantitative systems pharmacology (QSP) model integrating peripheral and liver cholesterol metabolism, as well as PCSK9 function, to examine the mechanisms of action of alirocumab and other lipid-lowering therapies, including statins. The model predicts changes in LDL-C and other lipids that are consistent with effects observed in clinical trials of single or combined treatments of alirocumab and other treatments. An exploratory model to examine the effects of lipid levels on plaque dynamics was also developed. The QSP platform, on further development and qualification, may support dose optimization and clinical trial design for PCSK9 inhibitors and lipid-modulating drugs. It may also improve our understanding of factors affecting therapeutic responses in different phenotypes of dyslipidemia and cardiovascular disease.

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.

Physical Chemistry of Bile: Detailed Pathogenesis of Cholelithiasis

Despite the overwhelming prevalence of cholelithiasis, many health care professionals are not familiar with the basic pathophysiology of gallstone formation. This article provides an overview of the biochemical pathways related to bile, with a focus on the physical chemistry of bile. We describe the important factors in bile synthesis and secretion that affect the composition of bile and consequently its liquid state. Within this biochemical background lies the foundation for understanding the clinical and sonographic manifestation of cholelithiasis, including the pathophysiology of cholesterol crystallization, gallbladder sludge, and gallstones. There is a brief discussion of the clinical manifestations of inflammatory and obstructive cholestasis and the impact on bile metabolism and subsequently on liver function tests. Despite being the key modality in diagnosing cholelithiasis, ultrasound has a limited role in the characterization of stone composition.

A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.

Investigating cholesterol metabolism and ageing using a systems biology approach

CVD accounted for 27 % of all deaths in the UK in 2014, and was responsible for 1·7 million hospital admissions in 2013/2014. This condition becomes increasingly prevalent with age, affecting 34·1 and 29·8 % of males and females over 75 years of age respectively in 2011. The dysregulation of cholesterol metabolism with age, often observed as a rise in LDL-cholesterol, has been associated with the pathogenesis of CVD. To compound this problem, it is estimated by 2050, 22 % of the world's population will be over 60 years of age, in culmination with a growing resistance and intolerance to pre-existing cholesterol regulating drugs such as statins. Therefore, it is apparent research into additional therapies for hypercholesterolaemia and CVD prevention is a growing necessity. However, it is also imperative to recognise this complex biological system cannot be studied using a reductionist approach; rather its biological uniqueness necessitates a more integrated methodology, such as that offered by systems biology. In this review, we firstly discuss cholesterol metabolism and how it is affected by diet and the ageing process. Next, we describe therapeutic strategies for hypercholesterolaemia, and finally how the systems biology paradigm can be utilised to investigate how ageing interacts with complex systems such as cholesterol metabolism. We conclude by emphasising the need for nutritionists to work in parallel with the systems biology community, to develop novel approaches to studying cholesterol metabolism and its interaction with ageing.

Obesity and the dysregulation of fatty acid metabolism: implications for healthy aging

The population of the world is aging. In 2010, an estimated 524 million people were aged 65 years or older representing eight percent of the global population. By 2050, this number is expected to nearly triple to approximately 1.5 billion, 16 percent of the world's population. Although people are living longer, the quality of their lives are often compromised due to ill-health. Areas covered: Of the conditions which compromise health as we age, obesity is at the forefront. Over half of the global older population were overweight or obese in 2010, significantly increasing the risk of a range of metabolic diseases. Although, it is well recognised excessive calorie intake is a fundamental driver of adipose tissue dysfunction, the relationship between obesity; intrinsic aging; and fat metabolism is less understood. In this review we discuss the intersection between obesity, aging and the factors which contribute to the dysregulation of whole-body fat metabolism. Expert commentary: Being obese disrupts an array of physiological systems and there is significant crosstalk among these. Moreover it is imperative to acknowledge the contribution intrinsic aging makes to the dysregulation of these systems and the onset of disease.

Cholesterol metabolism: A review of how ageing disrupts the biological mechanisms responsible for its regulation

Cholesterol plays a vital role in the human body as a precursor of steroid hormones and bile acids, in addition to providing structure to cell membranes. Whole body cholesterol metabolism is maintained by a highly coordinated balancing act between cholesterol ingestion, synthesis, absorption, and excretion. The aim of this review is to discuss how ageing interacts with these processes. Firstly, we will present an overview of cholesterol metabolism. Following this, we discuss how the biological mechanisms which underpin cholesterol metabolism are effected by ageing. Included in this discussion are lipoprotein dynamics, cholesterol absorption/synthesis and the enterohepatic circulation/synthesis of bile acids. Moreover, we discuss the role of oxidative stress in the pathological progression of atherosclerosis and also discuss how cholesterol biosynthesis is effected by both the mammalian target of rapamycin and sirtuin pathways. Next, we examine how diet and alterations to the gut microbiome can be used to mitigate the impact ageing has on cholesterol metabolism. We conclude by discussing how mathematical models of cholesterol metabolism can be used to identify therapeutic interventions.

Cardiometabolic risk in young adults from northern Mexico: Revisiting body mass index and waist-circumference as predictors

BACKGROUND

A body mass index (BMI) ≥30 kg/m(2) and a waist circumference (WC) ≥80 cm in women (WCF) or ≥90 cm in men (WCM) are reference cardiometabolic risk markers (CMM) for Mexicans adults. However, their reliability to predict other CMM (index tests) in young Mexicans has not been studied in depth.

METHODS

A cross-sectional descriptive study evaluating several anthropometric, physiological and biochemical CMM from 295 young Mexicans was performed. Sensitivity (Se), specificity (Sp) and Youden's index (J) of reference BMI/WC cutoffs toward other CMM (n = 14) were obtained and their most reliable cutoffs were further calculated at Jmax.

RESULTS

Prevalence, incidence and magnitude of most CMM increased along the BMI range (p < 0.01). BMI explained 81 % of WC's variance [Se (97 %), Sp (71 %), J (68 %), Jmax (86 %), BMI = 30 kg/m(2)] and 4-50 % of other CMM. The five most prevalent (≥71 %) CMM in obese subjects were high WC, low HDL-C, and three insulin-related CMM [Fasting insulin, HOMA-IR, and QUICKI]. For a BMI = 30 kg/m(2), J ranged from 16 % (HDL-C/LDL-C) to 68 % (WC), being moderately reliable (Jmax = 61-67) to predict high uric acid (UA), metabolic syndrome (MetS) and the hypertriglyceridemic-waist phenotype (HTGW). Corrected WCM/WCF were moderate-highly reliable (Jmax = 66-90) to predict HTGW, MetS, fasting glucose and UA. Most CMM were moderate-highly predicted at 27 ± 3 kg/m(2) (CI 95 %, 25-28), 85 ± 5 cm (CI 95 %, 82-88) and 81 ± 6cm (CI 95 %, 75-87), for BMI, WCM and WCF, respectively.

CONCLUSION

BMI and WC are good predictors of several CMM in the studied population, although at different cutoffs than current reference values.

Cholesterol absorption and synthesis markers in Portuguese hypercholesterolemic adults: A cross-sectional study

OBJECTIVE

The dynamics of cholesterol homeostasis and the development of cardiovascular disease (CVD) are complex and multifactorial, to which adds individual variability in the proportion of cholesterol from exogenous versus endogenous sources. The aim of this study was to undertake the first characterization of cholesterol absorption and synthesis profiles in Portuguese hypercholesterolemic adults through the quantification of surrogate markers, and the analysis of the predictive value of age and sex on the cholesterol homeostasis biomarkers.

METHODS

Serum samples for the measurement of lipid profiles and cholesterol homeostasis markers were obtained for 100 men and 112 women, aged 30-65, with TC ≥ 5.2 mmol/L (~200mg/dL) and/or LDL-C ≥ 2.6 mmol/L (~100mg/dL), none of whom were on any lipid-lowering therapy.

RESULTS

Overall, sex-specific significant differences were observed in the cholesterol homeostasis markers and lipid profiles; women had lower cholesterol synthesis marker concentrations (P<0.01 for lathosterol) and lipid parameters (except for HDL-C concentrations). Age-related significant differences were also found, including higher concentrations of cholesterol absorption markers in association with increasing age.

CONCLUSION

In our study, the predictors of higher levels of cholesterol absorption markers were higher age and female gender.

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.

Revisiting Human Cholesterol Synthesis and Absorption: The Reciprocity Paradigm and its Key Regulators

Hypercholesterolemia is a major risk factor for cardiovascular disease. Cholesterol homeostasis in the body is governed by the interplay between absorption, synthesis, and excretion or conversion of cholesterol into bile acids. A reciprocal relationship between cholesterol synthesis and absorption is known to regulate circulating cholesterol in response to dietary or therapeutic interventions. However, the degree to which these factors affect synthesis and absorption and the extent to which one vector shifts in response to the other are not thoroughly understood. Also, huge inter-individual variability exists in the manner in which the two systems act in response to any cholesterol-lowering treatment. Various factors are known to account for this variability and in light of recent experimental advances new players such as gene-gene interactions, gene-environmental effects, and gut microbiome hold immense potential in offering an explanation to the complex traits of inter-individual variability in human cholesterol metabolism. In this context, the objective of the present review is to provide an overview on cholesterol metabolism and discuss the role of potential factors such as genetics, epigenetics, epistasis, and gut microbiome, as well as other regulators in modulating cholesterol metabolism, especially emphasizing the reciprocal relationship between cholesterol synthesis and absorption. Furthermore, an evaluation of the implications of this push-pull mechanism on cholesterol-lowering strategies is presented.

Revisiting Human Cholesterol Synthesis and Absorption: The Reciprocity Paradigm and its Key Regulators

Hypercholesterolemia is a major risk factor for cardiovascular disease. Cholesterol homeostasis in the body is governed by the interplay between absorption, synthesis, and excretion or conversion of cholesterol into bile acids. A reciprocal relationship between cholesterol synthesis and absorption is known to regulate circulating cholesterol in response to dietary or therapeutic interventions. However, the degree to which these factors affect synthesis and absorption and the extent to which one vector shifts in response to the other are not thoroughly understood. Also, huge inter-individual variability exists in the manner in which the two systems act in response to any cholesterol-lowering treatment. Various factors are known to account for this variability and in light of recent experimental advances new players such as gene-gene interactions, gene-environmental effects, and gut microbiome hold immense potential in offering an explanation to the complex traits of inter-individual variability in human cholesterol metabolism. In this context, the objective of the present review is to provide an overview on cholesterol metabolism and discuss the role of potential factors such as genetics, epigenetics, epistasis, and gut microbiome, as well as other regulators in modulating cholesterol metabolism, especially emphasizing the reciprocal relationship between cholesterol synthesis and absorption. Furthermore, an evaluation of the implications of this push-pull mechanism on cholesterol-lowering strategies is presented.

Mosaic gene network modelling identified new regulatory mechanisms in HCV infection

Modelling of gene networks is widely used in systems biology to study the functioning of complex biological systems. Most of the existing mathematical modelling techniques are useful for analysis of well-studied biological processes, for which information on rates of reactions is available. However, complex biological processes such as those determining the phenotypic traits of organisms or pathological disease processes, including pathogen-host interactions, involve complicated cross-talk between interacting networks. Furthermore, the intrinsic details of the interactions between these networks are often missing. In this study, we developed an approach, which we call mosaic network modelling, that allows the combination of independent mathematical models of gene regulatory networks and, thereby, description of complex biological systems. The advantage of this approach is that it allows us to generate the integrated model despite the fact that information on molecular interactions between parts of the model (so-called mosaic fragments) might be missing. To generate a mosaic mathematical model, we used control theory and mathematical models, written in the form of a system of ordinary differential equations (ODEs). In the present study, we investigated the efficiency of this method in modelling the dynamics of more than 10,000 simulated mosaic regulatory networks consisting of two pieces. Analysis revealed that this approach was highly efficient, as the mean deviation of the dynamics of mosaic network elements from the behaviour of the initial parts of the model was less than 10%. It turned out that for construction of the control functional, data on perturbation of one or two vertices of the mosaic piece are sufficient. Further, we used the developed method to construct a mosaic gene regulatory network including hepatitis C virus (HCV) as the first piece and the tumour necrosis factor (TNF)-induced apoptosis and NF-κB induction pathways as the second piece. Thus, the mosaic model integrates the model of HCV subgenomic replicon replication with the model of TNF-induced apoptosis and NF-κB induction. Analysis of the mosaic model revealed that the regulation of TNF-induced signaling by the HCV network is crucially dependent on the RIP1, TRADD, TRAF2, FADD, IKK, IκBα, c-FLIP, and BAR genes. Overall, the developed mosaic gene network modelling approach demonstrated good predictive power and allowed the prediction of new regulatory nodes in HCV action on apoptosis and the NF-κB pathway. Those theoretical predictions could be a basis for further experimental verification.

Nutritional systems biology of type 2 diabetes

Type 2 diabetes (T2D) has become an increasingly challenging health burden due to its high morbidity, mortality, and heightened prevalence worldwide. Although dietary and nutritional imbalances have long been recognized as key risk factors for T2D, the underlying mechanisms remain unclear. The advent of nutritional systems biology, a field that aims to elucidate the interactions between dietary nutrients and endogenous molecular entities in disease-related tissues, offers unique opportunities to unravel the complex mechanisms underlying the health-modifying capacities of nutritional molecules. The recent revolutionary advances in omics technologies have particularly empowered this incipient field. In this review, we discuss the applications of multi-omics approaches toward a systems-level understanding of how dietary patterns and particular nutrients modulate the risk of T2D. We focus on nutritional studies utilizing transcriptomics, epigenomomics, proteomics, metabolomics, and microbiomics, and integration of diverse omics technologies. We also summarize the potential molecular mechanisms through which nutritional imbalances contribute to T2D pathogenesis based on these studies. Finally, we discuss the remaining challenges of nutritional systems biology and how the field can be optimized to further our understanding of T2D and guide disease management via nutritional interventions.