# Using colloborative cross mice to monitor resilience to malaria

> **NIH NIH R21** · STANFORD UNIVERSITY · 2020 · $236,396

## Abstract

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.

## Key facts

- **NIH application ID:** 9982778
- **Project number:** 5R21AI145365-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** David S. Schneider
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $236,396
- **Award type:** 5
- **Project period:** 2019-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9982778

## Citation

> US National Institutes of Health, RePORTER application 9982778, Using colloborative cross mice to monitor resilience to malaria (5R21AI145365-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/9982778. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*