The goal of this project is to identify host molecular signatures-particularly protein biomarkers and genetic variants-that influence inter-individual differences in COVID-19 severity and immune response. Using UK Biobank’s large-scale plasma proteomics data generated by the Olink platform, we will examine differential protein expression patterns associated with COVID-19 outcomes and relate them to clinical risk factors and outcomes. We also aim to integrate the proteomic data with external immunogenetic datasets, including genome-wide association study (GWAS) results and expression quantitative trait loci (eQTL) findings, to uncover shared molecular mechanisms that may predispose individuals to severe COVID-19 or alter vaccine responsiveness. Special emphasis will be placed on inflammation-related proteins, interferon signaling, and cytokine profiles. This work will improve understanding of the systemic immune responses associated with infection, aid in the identification of at-risk individuals, and help to prioritize therapeutic targets and predictive biomarkers for future pandemics or immunomodulatory interventions.
