Our overarching goal is to improve our resilience to infections. This will limit the pathology we suffer when we get ill and will ensure that we recover from our infections. We focus on malaria because this disease remains a serious human health problem. Malaria causes disease in hundreds of millions of children each year and kills hundreds of thousands. Malaria has this high absolute mortality because it infects so many, even though most children are resilient to the infection. Rather than trying to eliminate these hundreds of millions of infections, we are concentrating on ways of increasing resilience among malaria?s sickest victims. Our plan is to understand how resilience varies by recreating this variation using a mouse malaria model. We plan to infect mice with Plasmodium chabaudi and to identify mouse strains from the collaborative cross that show different symptoms because the collection contains a broad range of genetic variation. We will then correlate the immune response through the infection and metabolites at peak pathology to identify biomarkers for severe pathology. In the future, we will try manipulating these biomarkers to determine which can serve as levers for altering pathology. We have preliminary data supporting our approach. We?ve completed an analysis of the 8 parents of the collaborative cross and find that they differ in their response to this pathogen and that we can find metabolites that correlate with disease severity. We?ve modulated three of these metabolites and their signaling pathways and find that they can alter the outcome of infections. We have also monitored 492 P. chabaudi infected diversity outbred mice. These mice are the offspring of the collaborative cross. We found that the DO mouse population has a fine-grained continuum of phenotypes for malaria and that we can map three loci that control the anemia, survival and hypothermia resulting from this infection. Together these results suggest that there is considerable genetic variation in the response to malaria in this mouse population, that we can find significant biomarker hits using only 8 mouse strains, and that some of these hits can be used to modify disease outcomes. Our goal in this proposal is to increase the number of mouse strains we can use in our analysis by identifying collaborative cross lines that are spread out along the full range of malaria phenotypes. This will increase the power of our analyses as we try to identify biomarkers and drug targets for pathogenesis.
