Integrative omics to understand human immune variation

On a daily basis, millions of microorganisms enter our bodies and interact with us. As such, we have evolved a series of defense mechanisms that seek and destroy unfriendly microorganisms, known as our immune system. If our immune system is not well-calibrated and responds too slowly to microorganisms, we become susceptible to infections; on the other hand, if it responds too strongly it can damage our own body. Each and everyone of us has a slight variation in the calibration of our immune system, which is dependent on our genetics, lifestyle and environment; yet it is still not clear what is the role of this variation in health and disease. Therefore, in this thesis we aimed to expand our understanding of the variation of the immune system by integrating multiple layers of biological information. In the first section of this thesis, we focused on exploring the main drivers of such variation by looking at the levels of circulating immune cells and their responses after they encounter certain microorganisms. We were able to predict certain immune responses in healthy individuals using solely genetics. In the second section, we explored the role of gene expression levels of immune cells to understand their role in health and disease. We first evaluated the impact of genetics on gene expression in immune cells by developing a new computational approach. Last, we characterized the changes of gene expression over time after their stimulation with disease-relevant molecules using patient derived immune cells.

Dissertation: http://hdl.handle.net/11370/24cf7983-659c-453b-9f5f-682f6798a97b