Exploring Plasmodium falciparum genetic diversity to understand malaria immunity and infection risk

Abstract

Plasmodium parasites, the causative agents of malaria, have a complex evolutionary history involving their arthropod vectors, vertebrate hosts, and environment. Plasmodium falciparum is the deadliest of these malaria parasites, causing the deaths of hundreds of thousands of humans each year. In malaria-endemic settings, humans do not develop sterilizing immunity to P. falciparum infection; instead, naturally acquired immunity (NAI) against symptomatic or severe disease builds with repeated exposure. Most of the P. falciparum genome is not diverse, except for small regions within antigens with extremely high diversity. For this diversity to be maintained in parasite populations, it must offer some level of fitness advantage. These pockets of diversity are thought to be the result of diversifying selection imposed by the human immune system, but it is less understood how the acquisition of immunity relies upon or interacts with these antigenic regions. In this work, we explore the diversity of P. falciparum parasites in natural infections within a longitudinal cohort, seeking to understand how parasite genetic diversity may reflect natural immunity. In Chapter 1, we review the current state of genomic surveillance for P. falciparum, as well as what is known about naturally acquired immunity and infection risk. In Chapter 2, we develop two methods for studying genetic diversity within P. falciparum. We compare these to other targeted sequencing methods and evaluate the best methods for a variety of use cases, including studies of relatedness, complexity of infection, and geographic attribution. In Chapter 3, we begin to explore genetic data that we generated from a longitudinal cohort from malaria-endemic Mali. We search these data for potential genetic signals of naturally acquired immunity, including natural infection duration, asymptomatic period length, and complexity of infection. In Chapter 4, we determine the molecular force of infection for each individual over the years of the longitudinal study. We then use those data to evaluate the heterogeneity of infection risk and explore potential contributors to this heterogeneity. Finally, in Chapter 5, we explore these findings in the broader context of malaria genomics and public health. We consider the potential limitations of this work, as well as explore potential next steps for these questions.