B4642 - Meta-analysis of COVID-19 Vaccine Genetics - 20/06/2024

B number: 
B4642
Principal applicant name: 
Alexander J Mentzer | University of Oxford (United Kingdom)
Co-applicants: 
Bana Alamad, Fergus Hamilton
Title of project: 
Meta-analysis of COVID-19 Vaccine Genetics
Proposal summary: 

During the COVID-19 pandemic, vaccination efforts were crucial in controlling the spread of SARS-CoV-2. While we know from previous studies that factors including older age, immunosuppression, and obesity contribute to a reduced response to vaccination and increase the risk of breakthrough infection. Host genetic variability is increasingly appreciated to contribute to vaccination variability but contemporary studies lack power and diversity of immune measure and participant inclusion to truly understand the contribution and mechanism of genetic effects. By using statistical genetics approaches this project aims to better understand the role genetics plays in determining response to COVID-19 vaccines in different populations. This analysis may provide valuable insights into the factors influencing vaccine efficacy and inform future vaccine design and deployment strategies worldwide.

Impact of research: 
There is an ongoing need to identify individuals who are at risk of mounting a low response to COVID-19 vaccination, determine underlying heritable, molecular, and immunological mechanisms driving this response, and finally functionally validate these genetic findings to identify cellular functions and pathways responsible for eliciting this variation in the immune response to vaccination. Furthermore, we currently don’t have an in-depth understanding of how the efficacy of COVID-19 vaccines differs between populations, this work will potentially provide valuable insights into the factors influencing vaccine efficacy and inform future vaccine design and deployment strategies worldwide.
Date proposal received: 
Tuesday, 18 June, 2024
Date proposal approved: 
Thursday, 20 June, 2024
Keywords: 
Genetics, Infection, Obesity, DNA sequencing, Gene mapping, GWAS, Statistical methods, BMI, Epigenetics, Genetics, Genomics, Genome wide association study, Immunity, Mendelian randomisation, Statistical methods