Autoimmunity is a complex disorder affecting over 20 million Americans. Unveiling the multi-step process leading to autoimmunity and ultimately the ability to effectively treat disease requires an in-depth understanding of the self-reactive lymphocytes and the mechanisms by which they evade tolerance and promote destruction of self-tissue. Although there has been a large accumulation of quantitative data on the dynamics of CD8 T cell responses following infection, much less is known about how naive CD8 T cells differentiate into various effector pathways, nor about global CD8 T cell gene expression changes during autoimmune disease. Our proposal seeks to combine experimental, computational and mathematical approaches to understand the initiation and development of distinct autoimmune diseases.
Aim 1 will quantitatively define the gene expression kinetics in spontaneous autoimmune models with multiple disease manifestations.
In Aim 2 we will expand this evaluation to several autoimmune models with some overlapping and distinct autoimmune disease outcomes to systematically define the genes and pathways that underlie immune abnormalities critical to the development of individual diseases and those that underlie multiple diseases. We will further compare these data to published patient data to focus on clinically relevant genes specific to distinct autoimmune disease pathologies.
In Aim 3 we will combine the results of Aim 1 and 2 with existing disease relevant data to mathematically model the establishment of disease-specific CD8 T cell effector subsets. We will validate this model using mouse adoptive transfer studies of disease induction. This mathematical model will enable us to predict the gene signatures driving CD8 T cell fate choices and triggering autoimmunity.
Autoimmune disease can have a rapid onset with an often unclear cause. In some cases the targets of the immune response and mechanisms of disease pathogenesis have been revealed, but largely the initiating events leading to autoimmunity are unknown. This proposal will combine experimental and computational approaches to address these unknowns in a systemic fashion to help define the basis of disease onset and T cell subsets influencing this process.
