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

Mathematically modelling the dynamics of cholesterol metabolism and ageing

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the UK. This conditionbecomes increasingly prevalent during ageing; 34.1% and 29.8% of males and females respectively, over 75years of age have an underlying cardiovascular problem. The dysregulation of cholesterol metabolism isinextricably correlated with cardiovascular health and for this reason low density lipoprotein cholesterol(LDL-C) and high density lipoprotein cholesterol (HDL-C) are routinely used as biomarkers of CVD risk. Theaim of this work was to use mathematical modelling to explore how cholesterol metabolism is affectedby the ageing process. To do this we updated a previously published whole-body mathematical model ofcholesterol metabolism to include an additional 96 mechanisms that are fundamental to this biologicalsystem. Additional mechanisms were added to cholesterol absorption, cholesterol synthesis, reversecholesterol transport (RCT), bile acid synthesis, and their enterohepatic circulation. The sensitivity of themodel was explored by the use of both local and global parameter scans. In addition, acute cholesterolfeeding was used to explore the effectiveness of the regulatory mechanisms which are responsible formaintaining whole-body cholesterol balance. It was found that our model behaves as a hypo-responderto cholesterol feeding, while both the hepatic and intestinal pools of cholesterol increased significantly.The model was also used to explore the effects of ageing in tandem with three different cholesterolester transfer protein (CETP) genotypes. Ageing in the presence of an atheroprotective CETP genotype,conferring low CETP activity, resulted in a 0.6% increase in LDL-C. In comparison, ageing with a genotypereflective of high CETP activity, resulted in a 1.6% increase in LDL-C. Thus, the model has illustrated theimportance of CETP genotypes such as I405V, and their potential role in healthy ageing

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

Identification of novel biomarkers and candidate genes associated to lipid traits : improving the lipid metabolism knowledge base

FH, the most common monogenic dyslipidaemia, is characterised by increased circulating LDL-C levels leading to premature cardiovascular disease when undiagnosed or untreated. Current guidelines support genetic testing in patients fulfilling clinical diagnostic criteria and cascade screening of their family members. However, about half of clinical FH patients do not present pathogenic variants in the known disease genes (LDLR, APOB, PCSK9), and these most likely suffer from polygenic hypercholesterolaemia, which translates into a relatively low yield of genetic screening programs. This project aimed to identify new biomarkers able to improve the distinction between monogenic and polygenic profiles. Using a machine-learning approach in a paediatric dataset, tested for disease causative genes and investigated with an extended lipid profile, we developed new models that classify FH patients with higher specificity than currently used methods. The best performing models incorporated parameters absent from the common FH clinical criteria, which rely only on TC and LDL-C. A hierarchical clustering analysis of the same dataset showed that the study population can be clearly divided in three groups of dyslipidaemic individuals, showing the complexity of the dyslipidaemic biological context and the need of an integrative and multidisciplinary approach for biomarker selection. Both clustering and modelling analysis have revealed that the extended lipid profile contains important biomarkers. The exploration of lipid metabolic pathways associated with the identified biomarkers allowed us to identify a set of related genes. Using additional information from public databases, including gene expression data, associated GWAS and GO terms, we defined a universe of lipid-related genes and molecular interactions relevant for the dyslipidaemic context and future genetic studies. All this information was used to establish a new lipid knowledge base available online. The obtained results can be applied to improve the yield of genetic screening programs and decrease the associated costs, and also provide novel contributions to our understanding of dyslipidaemias

A physiologically based kinetic model for the prediction of plasma cholesterol concentrations in mice and man

An increased plasma cholesterol concentration is associated with increased risk of cardiovascular disease. However, individuals vary largely in their response to cholesterol lowering drugs and 40% of them, do not reach their cholesterol-lowering target. Development of novel therapies, for example combinations of existing drugs, can be accelerated by more mechanistic understanding of cholesterol metabolism. This understanding can be improved using computational models. This thesis describes the development, validation, and analysis of a physiologically based kinetic (PBK) model for the prediction of plasma cholesterol concentrations in humans. For this purpose, first a PBK model for the mouse was set up, calibrated and validated, using ensemble modeling. Then the mouse model was converted to a model for humans. It describes the 21 most influential physiological reactions affecting cholesterol concentrations in 8 pools, including liver, HDL, and non-HDL. The model was parameterized using literature data and validated using clinical data for human mutations and drug interventions, taken from literature. The model was applied to find properties that determine the individual response to drugs. The processes: hepatic cholesterol synthesis, peripheral cholesterol synthesis, and hepatic cholesterol esterification were major determinants of the non-HDL-C response to the cholesterol-lowering drug pravastatin. We conclude that plasma cholesterol concentrations and effects of genetic polymorphisms and drugs thereupon can be predicted in silico and thatPBK modeling can provide novel mechanistic insights. </p

Flaxseed Lignan Metabolites Modulate Hepatocellular Cholesterol Trafficking In HepaRG

High blood cholesterol (HBC) is an important risk factor of cardiovascular disease (CVD), which is associated with high morbidity and mortality worldwide. Lifestyle changes and drugs (e.g. statins) are mainly advised by practitioners to manage cholesterol; however, safer alternatives such as natural products might be considered for mild to moderate hypercholesterolemia or in combination with statins in more severe conditions. The literature indicates the ability of flaxseed lignans to improve cholesterol blood profiles. However, the mechanism by which the metabolites of the non-bioavailable plant lignan, secoisolariciresinol diglucoside, modulate blood cholesterol levels is not yet known. This study examines a possible mechanism of cholesterol modulation in the liver that involves altered cholesterol trafficking based upon recent investigations in the Caco-2 cell line from my laboratory. In addition, the concomitant oral administration of statins and flaxseed lignans raises a possible role for a ‘drug-drug’ interaction at hepatic uptake transporters (OATP1B) which cannot be ignored as these transporters impact the pharmacokinetics and pharmacodynamics of statins. To address lignan mechanism of action, the effect of the mammalian lignan, enterolactone (ENL), and its metabolite, enterolactone glucuronide (ENL-Gluc), on hepatic trafficking of the fluorescent cholesterol probe NBD-cholesterol, was investigated using fluorescence microscopy in the HepaRG cell line as an in vitro liver model. Specific dye markers for endoplasmic reticulum was used to identify the intracellular location of cholesterol trafficking and accumulation. Furthermore, the INSIG-SREBP cholesterol regulation pathway was examined after treatment with ENL and ENL-Gluc by expression analysis of genes important in cholesterol metabolism and trafficking, namely, INSIG-1, SREBP-2, HMGCoA-reductase and LDL-receptor by qPCR and confirmed with western blot analysis. In addition, the possible inhibitory effect of ENL and ENL-Gluc on the uptake of the organic anion transporting polypeptide 1B1 and 1B3 substrate, fluorescein methotrexate (FMTX), was examined in HEK293 cells overexpressing human OATP1B1 & OATP1B3 transporters. Under high intracellular sterol conditions, both ENL and ENL-Gluc reduced the uptake of fluorescent cholesterol into HepaRG cells. In comparison to vehicle control (1% DMSO), treatment with 20 µM ENL and 20 µM ENL-Gluc reduced cholesterol uptake by 1.8 and 2.0-fold, respectively. This was confirmed by observing a surge in NBD-cholesterol accumulation in the endoplasmic reticulum (ER) following treatment with different concentrations of ENL and ENL-Gluc. These results suggest ENL and ENL-Gluc alter hepatocellular cholesterol homeostasis through increasing cholesterol retention within the endoplasmic reticulum. Furthermore, changes in the relative expression of multiple target genes that are responsible for activation of a membrane bound transcription factor, SREBP, as well as protein level measurements by western blot analysis suggest a transcriptional regulation of cholesterol biosynthesis via enhancement of HMGCoA-reductase degradation as well as inhibition of cholesterol uptake. Furthermore, the possible interaction between ENL or ENL-Gluc and hepatic uptake transporters OATP1B1 and OATP1B3 was observed by conducting an inhibitory uptake assay in HEK293 cells overexpressing human OATP1B1& OATP1B3 transporters. These investigations showed inhibition of probe substrate uptake by ENL and ENL-Gluc. In conclusion, we reported that flaxseed lignan ENL and its active glucuronidated form are suggested to be responsible for the modulation effect on cholesterol homeostasis and trafficking observed in HepaRG cells. Both ENL and ENL-Gluc showed a reduction in cholesterol uptake and an increase in cholesterol surge into the endoplasmic reticulum which involved downregulation of HMGCoA-R and LDL-R, and upregulation of SREBP-2, proteins of sterol sensing domain (SSD). This effect is apparently mediated via the active glucuronide form of ENL, which showed an inhibitory effect on OATP1B1 and OATP1B3 hepatic uptake-mediated statin transport. Further in vivo investigation is necessary to confirm the altered effect of lignans on cholesterol transport and metabolism as well as the inhibitory effect on OATP hepatic uptake transporters

Cardiovascular protective effect of cinnamon and its major bioactive constituents: An update

Cinnamon from the bark of Cinnamomum species is one of the most important spices used worldwide in food and as a traditional medicine for centuries. It has substantial benefits for human health including its protective role on cardiovascular diseases. This review provides an overview of the cardiovascular protective effects of cinna-mon and its major bioactive constituents. Reviewed literature showed sufficient evidence that cinnamon can reduce the risk of cardiovascular diseases, including cardiac ischemia, cardiac hypertrophy, and myocardial infarction. Furthermore, cinnamon exhibited beneficial effects on cardiovascular-related comorbidities like diabetes, and other metabolic disorders, and showed antioxidant and anti-inflammatory effects. Cinnamon contains several bioactive compounds such as phenolics and volatile compounds. Cinnamaldehyde and cinnamic acid are among the main cinnamon compounds with protective effects on cardiovascular diseases through different molecular mechanisms. Although the protective effects of cinnamon and its main compounds have been extensively reported, more preclinical and clinical studies are still required before its use as a biopharmaceutical agent.info:eu-repo/semantics/publishedVersio

Role of adipose tissue in the pathogenesis and treatment of metabolic syndrome

© Springer International Publishing Switzerland 2014. Adipocytes are highly specialized cells that play a major role in energy homeostasis in vertebrate organisms. Excess adipocyte size or number is a hallmark of obesity, which is currently a global epidemic. Obesity is not only the primary disease of fat cells, but also a major risk factor for the development of Type 2 diabetes, cardiovascular disease, hypertension, and metabolic syndrome (MetS). Today, adipocytes and adipose tissue are no longer considered passive participants in metabolic pathways. In addition to storing lipid, adipocytes are highly insulin sensitive cells that have important endocrine functions. Altering any one of these functions of fat cells can result in a metabolic disease state and dysregulation of adipose tissue can profoundly contribute to MetS. For example, adiponectin is a fat specific hormone that has cardio-protective and anti-diabetic properties. Inhibition of adiponectin expression and secretion are associated with several risk factors for MetS. For this purpose, and several other reasons documented in this chapter, we propose that adipose tissue should be considered as a viable target for a variety of treatment approaches to combat MetS

Methods in Computational Biology

Modern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled “Methods in Computational Biology”, is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections:•Reviews of Computational Methods•Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels•The Interface of Biotic and Abiotic Processes•Processing of Large Data Sets for Enhanced Analysis•Parameter Optimization and Measuremen