Title: Predicting infectious disease evolution in light of immune system diversity
Funder: The Academy of Medical Sciences

Abstract: 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. I will change this 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. My 3 major aims are as follows: Aim 1: Understand the rules governing pathogen evolution in the presence of HLA variation. Aim 2: Identify if HLA population genetics affects the emergence of novel SARS-CoV-2 variants AIM 3: Predict optimal antigens to use in Plasmodium falciparum vaccines. For aim 1 I will develop mathematical and computational models, including agent-based models in which pathogen antigens explicitly co-evolve with immunogenetically diverse host populations. I will use these models 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 I will combine the theoretical insights from aim 1 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). I 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.

Lay abstract: The way that my immune system responds to infection is unlikely to be exactly the same as yours. One reason for this is our genetics. We know that when someone needs an organ transplant, it’s important to find a tissue matched donor. Tissue matching means matching donor and recipient immune system genes. Finding a matched donor can be challenging, showing just how diverse our immune systems are. I research how immune system differences affect the way infectious diseases spread in populations. As we have seen during the COVID-19 pandemic, predicting pathogen evolution is extremely challenging. Understanding the interaction between human immune system diversity and pathogen evolution is crucial if we hope to make better predictions in the future. I will build mathematical and computational models which simulate how pathogens spread in genetically diverse populations, and use these to develop a thorough understanding of the different ways pathogens can behave. I will then use the insights I have gained to analyse pathogen and human genetic sequences, and predict which pathogen changes are occurring as a result of human immune system diversity. I will focus on SARS-CoV-2 (which causes COVID-19 and has only recently started infecting humans) and malaria (which has co-evolved with humans for a long time). Understanding the evolution of both of these pathogens will help us to treat and control them. By investigating two different (“old” and “new”) pathogens I also intend that broad insights from my work can be applied to a range of other infections.

Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT;5.1 PHARMACEUTICALS
Health categories: INFECTION