Multi-OMIC biomarkers to predict neonatal vaccine response

Many babies die within the first month of life from infectious diseases. Despite successful neonatal vaccination programs, it is not yet possible to accurately predict if a vaccine will work on a newborn child, at the individual “personalized” level. We need to better understand the mechanism of antibody generation after vaccination to improve immunization programs. This project will work in that direction by analyzing novel data obtained from neonates in The Gambia and then validate the findings with data from Papua New Guinea (PNG). We will explore genes (RNA), proteins, cytokines and immune cell datasets for molecular mechanisms and predictive biomarkers that indicate the antibody generation. These datasets will also be integrated to identify new areas of biological understanding that may not be identified in single dataset analysis. The results of this project will provide new perspectives to improve vaccine protocols across the world and aid in furthering the health care mission of the PROOF Centre (our partner organization).

Faculty Supervisor:

Scott Tebbutt;Bradley Quon


Abhinav Kumar Checkervarty


PROOF Centre of Excellence






University of British Columbia



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