The Systems Immunogenetics Project aims to use forward genetic screens, in models that recapitulate the genetic diversity found in humans, to better understand how natural variation and polygenic interactions regulate variable immune and disease outcomes in outbred populations. We argue that this theme is central for understanding the genetic regulation of the immune response, and this knowledge is essential for improving precision medicine, disease prediction, diagnosis, and treatment of humans.
Using a reproducible population of ~110 CC RIX lines (outbred but reproducible F1 crosses between CC-RI lines that model heterozygous human populations) our team has quantified baseline and virus-induced innate, adaptive, and inflammatory immune responses and disease outcomes over a 45 day time course (7-8 time points/3-5 mice per CC-RIX line) following infection with three viruses: Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Influenza A virus (IAV), and West Nile virus (WNV). To our knowledge, this represents the most comprehensive analysis of virus-induced immune responses ever conducted in a genetically variable complex mouse reference population, and the resulting data set (see Data Visualizations) provides an unprecedented resource for understanding how host genetic variation impacts immune and disease responses across multiple viral pathogens.
Having recently completed these screens, we have begun identifying quantitative trait loci (QTL)—host genome regions containing polymorphisms which impact aspects of the host immune response. Although we have analyzed only ~10% of the data, the program has already identified over 100 quantitative trait loci (QTL) that regulate both baseline (pre-exposure) immune phenotypes, as well as virus-induced innate and adaptive immunity, inflammation, and disease outcomes. This represents the largest collection of naturally divergent and polymorphic immune susceptibility loci ever mapped for any set of mammalian viruses.