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Connecting the dots between DNA, proteins, and disease: Identifying genetic variants and proteins relevant for studying venous thromboembolism

Abstract

In order to prospectively identify individuals at risk for disease, it is important to identify markers that can be reliably measured and to understand the relation of these markers to the disease. For venous thromboembolism (VTE), large-scale genetic studies have had limited success identifying genetic variants and proteins that contribute to disease risk. An alternative method is to focus on the intermediate steps between genetics and disease, such as protein levels. In this dissertation, we set out to identify genetic variants that contribute to blood protein levels and then identify blood proteins that can be used as biomarkers for venous thromboembolism. For the whole dissertation, we utilize the Tromsø Study, a single-center, prospective, study of the inhabitants of Tromsø, Norway. These individuals allow us to identify genetic variants and proteins that are associated with VTE before any symptoms of the disease start, which is key when trying to pre-emptively identify and treat individuals that are at risk for developing VTE. In chapter two, we measure cardiovascular-relevant serum proteins using enzyme-linked immunosorbent assays. We then identify common and rare genetic variation that is associated with the levels of these proteins. In chapter three, we measure the plasma proteome using tandem-mass-tagged mass spectrometry. We then identify common and rare genetic variation that is associated with the levels of these proteins. We further investigate the underlying mechanisms of how genetic variation regulates levels of plasma proteins. In chapter four, we utilize the same plasma proteome that was measured in chapter three in order to identify proteins that are associated with risk of venous thromboembolism. Together, this work advances our understanding of how genetic variants ultimately result in diseases, via their effects on intermediate protein levels.

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