The current health care system is severely challenged by for instance rising costs, fewer new blockbuster drugs and increasing numbers of hospitalizations due to side effects. Especially in the... Show moreThe current health care system is severely challenged by for instance rising costs, fewer new blockbuster drugs and increasing numbers of hospitalizations due to side effects. Especially in the area of chronic diseases the current disease fighting strategy is failing and a more personalized medicine approach is needed. In this thesis new sub-types of rheumatoid arthritis are characterized with metabolomics analysis and symptoms patterns. The sub-types are based on diagnostic knowledge from Chinese medicine. The two sub-types of RA patients were found to have differences in apoptosis regulation of T-cells and differences in urine acylcarnitine levels. A questionnaire was designed to distinguish the two sub-types and to evaluate symptom patterns of arthritis patients. In the future the response to treatment of these sub-types of patients can be studied and specific treatment can be targeted to these sub-types. Show less
This thesis was to combine metabolomics and Chinese medicine (CM) diagnosis to search for biomakers or metabolic profiles to subtype of type 2 diabetes (T2DM). An explorative study of 50 males with... Show moreThis thesis was to combine metabolomics and Chinese medicine (CM) diagnosis to search for biomakers or metabolic profiles to subtype of type 2 diabetes (T2DM). An explorative study of 50 males with pre-diabetes was designed and two subtypes (A and B) could be identified by urine metabolomics. More metabolic disturbances were indicated in subtype B. The effects of rimonabant and a multi-component preparation (SUB885C), both with reported effects of regulating weight and the improvement on metabolic risks, were assessed by lipidomics on ApoE*3Leiden.CETP Mice. A 4-week rimonabant intervention brought a significant weight reduction, but moderate effects on lipid profile. SUB885C was able to produce multiple anti-atherogenic changes in lipids of the mice to improve metabolic parameters. A combined approach of lipidomics, biochemistry and herbal component profiling was used to evaluate the effects of the ginseng roots of 3__6 years on the regulation of dyslipidemia in diabetic Goto-Kakizaki rats. The more than 4 year ginseng proved to be valuable for drug development to regulate lipids. To conclude, the early metabolomics investigations performed in this thesis converged analytical bioscience, clinical approach and the diagnostic perspectives in other health system to provide the systems biology view on the pre-stage of T2DM. Show less
The introduction of systems biology in combination with the profiling of numerous biochemical components (e.g. lipid metabolites, herbal products) enables the study of living systems from a... Show moreThe introduction of systems biology in combination with the profiling of numerous biochemical components (e.g. lipid metabolites, herbal products) enables the study of living systems from a holistic perspective. In this thesis we explored systems biology-based platforms to investigate the therapeutic effects of chemical drugs and herbal medicines on animal models with high-fat diet-induced obesity and genetic manipulated diabetes. The aim of the work was to better understand the working mechanisms of both treatments on metabolic syndrome from a holistic point of view and to evaluate the potentials of __omics__ technologies to this effort. Our results showed that lipidomics approach with appropriate bioinformatics tools are essential to describe the global, dynamic metabolic response of living systems, e.g. from homeostasis via sub-optimal health and ultimately to dysfunction. These studies pointed hints to disco ver lipid biomarkers in relation to health promotion and disease prevention and facilitated the understanding of the complex regulatory mechanisms in humans or animals. Particularly, the introduction of the systems biology view will not only provide in-depth insights into the multi-target synergetic effects (which have hardly been used in modern drug discovery) but also can bridge Chinese Medicine (multi-target therapy) and Western Medicine (molecular pharmacology). Show less
This dissertation mainly focuses on interdisciplinary approaches for biomedical knowledge discovery. This required special efforts in developing systematic strategies to integrate various data... Show moreThis dissertation mainly focuses on interdisciplinary approaches for biomedical knowledge discovery. This required special efforts in developing systematic strategies to integrate various data sources and techniques, leading to improved discovery of mechanistic insights on human diseases. Chapter one looks at the possibility in which combining various bioinformatics-based strategies can significantly improve the characterization of the OPMD mouse model. We discuss that this approach in knowledge discovery, on the basis of our extensive analysis, helped us to shed some light on how this model system relates to OPMD pathophysiology in human. In Chapter two, we expand on this combinatory approach by conducting a cross-species data analysis. In this study, we have looked for common patterns that emerge by assessing the transcriptome data from three OPMD model systems and patients. This strategy led to unravelling the most prominent molecular pathway involved in OPMD pathology. The third chapter achieves a similar goal to identify similar molecular and pathophysiological features between OPMD and the common process of skeletal muscle ageing. Engaging in a study in which the focus was made on the universality of biological processes, in the light of evolutionary mechanisms and common functional features, led to novel discoveries. This work helped us uncover remarkable insights on molecular mechanisms of ageing muscles and protein aggregation. Chapters four and five take a different route by tackling the field of computational biology. These chapters aim to extend network inference by providing novel strategies for the exploitation and integration of multiple data sources. We show that these developments allow us to infer more robust regulatory mechanisms to be identified while translations and predictions are made across very different datasets, platforms, and organisms. Finally, the dissertation is concluded by providing an outlook on ways the field of systems biology can evolve in order to offer enhanced, diversified and robust strategies for knowledge discovery. Show less
