PhD defence: Untargeted metabolomics and data analysis strategies to discover biomarkers
Qian Gao is defending her PhD thesis
Untargeted metabolomics and data analysis strategies to discover biomarkers
20 December 2018, 13:00
Auditorium A1-01.01, Festauditoriet, Bülowsvej 17, Frederiksberg.
Associate Professor Faidon Magkos (chair), Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
Professor Rikard Landberg, Food and Nutrition Science, Chalmers University of Technology, Sweden
Professor Hanne Christine S. Bertram, Department of Food Science, Aarhus University, Denmark
Professor Lars Dragsted, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
Associate Professor Timothy Ebbels, Department of Surgery & Cancer, Faculty of Medicine Imperial College London, United Kingdom
About the thesis
Biomarkers are a useful tool to measure exposures and their biological effects and to evaluate system susceptibility. They have been widely applied in the nutrition area to evaluate dietary intake and its resulting biological consequences and the nutritional status of the study subjects. However, the existing classification schemes of biomarkers are ambiguous leading to uncertainty about their application. With the development of metabolomics technology, the biomarker research field is experiencing rapid changes and new biomarkers are continuously discovered. Challenges also emerge as metabolomics data is large scale, noisy and complex. Therefore, efficient data analysis tools are needed to extract the most relevant information from it.
In this thesis, a classification scheme for the currently applied and newly discovered dietary and health biomarkers in the nutrition field is developed, the data analysis strategy in untargeted metabolomics studies is optimized for the more precise discovery of biomarkers and applied for the discovery of biomarkers related to onion consumption.
We developed an improved scheme for biomarker classification based on their intended use rather than the technology or outcomes and suggested six subclasses. For the discovery of exposure biomarkers, different bi- and trilinear PLS models for variable selection in untargeted metabolomic studies were compared. Bilinear PLS model with group × time-response as dummy Y showed the best performance. This model has been applied in an onion intervention study and eight biomarkers of onion intake have been successfully discovered.
2018, 160 pages
The thesis is available for inspection at the library, Nørre Allé 51, DK-2200 Copenhagen N.