Use of multimodel omics technologies to study Dengue host response markers

Dengue virus is one of the top 10 global health threats, with about half of the world’s population at risk of being infected. Infection occurs through the bite of an infected mosquito. Most infections manifest themselves as a mild form of the disease, limited to fever, headache, and lower back pain. However, 500,000 dengue cases require hospitalization (severe dengue) and up to 25,000 patients die due to dengue annually.
Despite the high incidence, the impact of dengue infection in humans remains insufficiently understood and no biological markers have been identified that can accurately predict who will develop severe dengue. To address these gaps in the current knowledge, this project will use state-of-the-art laboratory and data science techniques to generate a detailed map of the impact of dengue infection on the host at several levels (including protein expression, gene expression, and immune response). We will investigate which of these factors are linked to severity of disease, and more particularly, we search for markers that may predict the development of severe dengue and related complications.
This work will result in a better understanding of how the body responds to dengue infection, and how this relates to the manifestation and severity of symptoms. Importantly, this project will also lead to the identification of better markers to predict progression to severe dengue. Additionally, this work might lead to new treatment options, especially for severe dengue.