Severe and emerging respiratory virus infections are responsible for considerable human morbidity and mortality and threaten global health. Importantly, significant individual to individual variation in immune responses after infection regulates disease severity, a process that is heavily influenced by natural host genetic variation in human populations. In this backdrop, new paradigms are needed to achieve the promise of precision medicine, early disease diagnosis/prognosis, susceptibility and risk assessment, and personalized treatment. To address this theme, our research programs leverage forward genetic screens in the newly developed collaborative cross (CC) mouse resource to map, identify, and elucidate the polygenic immune interactions and molecular mechanisms that govern disease severity following highly pathogenic respiratory virus infection. Using the SARS-CoV model, natural genetic variation in the CC expands the range and composition of respiratory disease phenotypes, corresponding to selective forces that have shaped human immunity.
Aim 1 seeks to define quantitative trait loci governing immunity to SARS-CoV and related viruses.
Aim 2 identifies causal gene candidates within the QTL and seeks to derive mechanistic insights. Finally, Aim 3 integrates these findings across different disease models and between mouse models and human patients. Overall, the goal is to identify the mechanism by which polygenetic traits drive differential disease, to predict and then test disease outcomes in genetically distinct lines that contain different admixtures of susceptibility loci, and to integrate these findings across diverse disease models and species.
Using the genetically diverse Collaborative Cross mouse resource, we identify quantitative trait loci dictating immunity and pathogenesis following SARS-CoV infection. On going work seeks to identify causal genes driving phenotypic outcomes, link these findings to other disease models, and facilitate translation for improvement of human health.
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