Computational modeling of lipoprotein metabolism

Abstract

This PhD thesis contains the following chapters. The first part, containing chapter 2 and 3 mainly concerns model development. Chapter 2 describes the development of a mathematical modeling framework within which different diagnostic models based on lipoprotein profiles can be developed, and a first validation of a model in this framework using data from a stable__isotope flux study (78). Chapter 3 describes a further development of the model, and the development of a new lipoprotein model__based candidate diagnostic and its validation using a range of stable__isotope flux studies. The second part, containing chapter 4, 5, and 6, concerns model applications. Chapter 4 contains the first application of the model__based candidate diagnostic using HPLC__measured lipoprotein profiles, in the context of a nutritional intervention study conducted at TNO. Chapter 5 contains an exploration of lipoprotein profile data from a population study (the GOLDN study), and examines how subgroups of patients, identified via K__means clustering based on lipoprotein profiles, differ in their lipid response to a fenofibrate intervention. It also examines how the model__based candidate diagnostic behaves in these subgroups. Chapter 6 contains the study that shows that lipoprotein metabolism indicators may have predictive value for cardiovascular risk on top of classical risk markers. Chapter 7 contains a methodological reflection on the development of computational models for clinical diagnostic use based on clinical chemistry data. Finally, chapter 8 contains a general discussion of the research presented in this PhD thesis and suggestions for further research