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Investigating cholesterol metabolism and ageing using a systems biology approach

Published online by Cambridge University Press:  02 November 2016

A. E. Morgan
Affiliation:
Department of Chemical Engineering, University of Chester, Thornton Science Park, Chester CH2 4NU, UK
K. M. Mooney
Affiliation:
Faculty of Health and Social Care, Edge Hill University, Ormskirk, Lancashire L39 4QP, UK
S. J. Wilkinson
Affiliation:
Department of Chemical Engineering, University of Chester, Thornton Science Park, Chester CH2 4NU, UK
N. A. Pickles
Affiliation:
Department of Biological Sciences, University of Chester, Parkgate Road, Chester CH1 4BJ, UK
M. T. Mc Auley*
Affiliation:
Department of Chemical Engineering, University of Chester, Thornton Science Park, Chester CH2 4NU, UK
*
* Corresponding author: M. T. Mc Auley, email m.mcauley@chester.ac.uk
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Abstract

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.

Information

Type
Conference on ‘New technology in nutrition research and practice’
Copyright
Copyright © The Authors 2016 
Figure 0

Fig. 1. UK life expectancy by year of birth. Data from Clio-Infra(132).

Figure 1

Fig. 2. (Colour online) UK population by age and sex in 1982 and 2012. Data from United Nations Statistics Division(133).

Figure 2

Fig. 3. (Colour online) UK causes of death by age. Data from British Heart Foundation(134).

Figure 3

Fig. 4. (Colour online) Modelling overview. (1) Identify the system to model and hypothesis formation. (2) Identify pre-existing models; using the BioModels Database, a repository for peer reviewed models. (3) If no model of the system of interest exists: produce a network diagram. If a model does exist: download model and move to step 5, then step 7. (4) Establish mathematical framework. (5) Identify a suitable modelling tool; there are several available including: COPASI, which we utilised in our updated model of cholesterol metabolism(123), CellDesigner, Mathematica and MATLAB. (6) Obtain initial concentrations of species, rate laws and kinetic data to construct the model. The online resources BRENDA and SABIO-RK provide a substantial volume of kinetic data. (7) Run simulations. (8) Validate the model. (9) Explore the hypotheses, and determine if the model accurately represents the biological system, and can be used to make predictions, or if the model needs refining. (10) Conduct further wet laboratory experiments based upon model output. (11) Code the model in the exchange format, Systems Biology Markup Language and deposit in the BioModels Database. Adapted from Mc Auley and Mooney(135).

Figure 4

Fig. 5. (Colour online) Overview of age-related changes to cholesterol metabolism.

Figure 5

Fig. 6. (Colour online) UK prescription drugs for CVD. Data from British Heart Foundation(134).

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Fig. 7. Model simulation of ageing in the presence of cholesteryl ester transfer protein genotypes. Taken from Morgan et al.(123).