Lipid signaling is an essential biological event/process in a plethora of pathophysiological conditions. The underlying idea of this thesis is that many of the roles and the complex interplay of... Show moreLipid signaling is an essential biological event/process in a plethora of pathophysiological conditions. The underlying idea of this thesis is that many of the roles and the complex interplay of the individual signaling lipids in inflammatory processes and related conditions in health and disease is not well known, and therefore has to be studied integrally as a complex network. In order to study this complex interplay, an improved broad analytical method is necessary to analyze a wide range of different signaling lipid classes such as oxylipins, (nitro) free fatty acids, endocannabinoids, bile acids and different subclasses of lysophospholipids. Therefore, the aim of this thesis is to develop a better method to study signaling lipids, and to apply it to study the role of these molecules in several relevant biological questions for a better understanding of inflammation related pathophysiology including autoimmune diseases, neurodegeneration and regulatory effect of exercise training. Show less
Neurodegenerative diseases, including Parkinson’s disease (PD), are increasing in prevalence due to the aging population. Despite extensive study, these diseases are still not fully understood and... Show moreNeurodegenerative diseases, including Parkinson’s disease (PD), are increasing in prevalence due to the aging population. Despite extensive study, these diseases are still not fully understood and the lack of personalised treatment options that can target the cause of the diseases, rather than the symptoms, has led to a greater demand for improved disease understanding, therapies and diagnostic procedures. In this thesis, we use systems biology approaches to construct disease-specific models intended for biomarker discovery, therapeutic treatment strategy identification and drug repurposing in PD. Systems biology is a mathematical field of research that analyses biological systems via construction of a computational model using experimental data. This is achieved by integration of omics data, including genomics, proteomics, transcriptomics and metabolomics. A specific approach used to identify the physico- and biochemical bounds within a biological system is constraint-based modelling, which requires the input of absolute quantitative metabolomics data. To improve our absolute quantitative coverage of the metabolome, we developed and improved new quantitative metabolomics methods using a targeted mass spectrometry workflow to obtain data intended to be integrated into constraint-based metabolic models for the study of PD. Show less
