Predicting infectious disease evolution in light of immune system diversity

Immunogenetic diversity, including Human Leukocyte Antigen (HLA) diversity affects how individuals and populations respond to infectious diseases. However, beyond the study of one particular infection (HIV), HLA immunogenetics are little considered in infectious disease epidemiology. This will be changed by developing generalisable models of infectious diseases in immunogenetically diverse populations, and applying the insights from these models to two specific infectious diseases: SARS-CoV-2 and malaria.

For aim 1 mathematical and computational models will be developed, including agent-based models in which pathogen antigens explicitly co-evolve with immunogenetically diverse host populations. These models will then be used to (i) ascertain the range of possible pathogen behaviours in light of HLA genetic diversity and (ii) develop test statistics to identify regions of pathogen proteins that are likely HLA-restricted epitopes. For aims 2 and 3 the theoretical insights from aim 1 will be combined with novel analyses of population genetic and bioinformatics datasets in order to make specific predictions about SARS-CoV-2 (aim 2) and P. falciparum malaria (aim 3). This project will use HLA population genetic data from allelefrequencies.net; SARS-CoV-2 genomic data from the GISAID database and P. falciparum genomic data from the Malariagen project.

Project details

Genetics and Genomics
Immunology

Jun 2022 — May 2024

$123,181

United Kingdom