IgE antibody responses to the oligosaccharide galactose-alpha-1,3-galactose (alpha-gal) in murine and human atherosclerosis

University Of Virginia, Charlottesville VA

Investigators

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Abstract

Project Summary Increased total serum IgE levels are associated with coronary artery disease (CAD). However, the causal role of antigen-specific IgE in CAD remains largely unexplored. Recent work from our group and others provide evidence that humans with IgE sensitization to the mammalian oligosaccharide allergen a-gal have larger coronary artery plaques and unstable plaque features signifying increased CAD compared to those without IgE to a-gal. Despite these compelling human associative findings, no study to date has investigated the role of antigen-specific IgE as a driver of CAD severity and the molecular and cellular mechanisms mediating IgE sensitization to a-gal linked to atherosclerosis. We recently reported that humans with IgE sensitization to a-gal had a higher frequency of CCR6+ switched memory (SWM) B cells. Notably, consistent with the association of the IgE sensitization to a-gal and CAD, the amount of CCR6 on SWM B cells was associated with CAD severity. Transcriptomic analysis demonstrated that CCR6+ SWM B cells expressed higher IL-4R and STAT6 in subjects that were IgE a-gal+ compared to IgE a-gal-. Interestingly, IL-4 and STAT6 are important for B cell class switch recombination to IgE, suggesting that cells that make IL-4 may be important in IgE to a-gal production. Preliminary data using a novel mouse model deficient in NKT cells that are early producers of IL-4 show reduced levels of IgE to a-gal and implicates invariant NKT cells in the regulation of IgE antibody production to a-gal. Based on these human and murine data, the overarching objective of the parent grant is to investigate whether these factors and cells play a causal role in atherosclerosis development due to IgE sensitization to a-gal. A major component of these studies is to analyze single cell mass cytometry data derived from PBMCs of a second, independent and larger cohort of humans with CAD sensitized to a-gal allowing for more robust multivariate analysis and deeper interrogation of immune cell phenotypes that mark those at greatest risk. The overall goal of this research supplement is to make the mass cytometry data AI-ready with associated datasheets that contain the cell subtype annotations, protein type and activation state markers, cohort statistics, CAD severity measures and other relevant clinical variables (e.g., age, sex, smoking status, etc.). We will prepare noise filtered, normalized, batch corrected, cell type annotated CAD patient single cell mass cytometry data for AI applications and use an explainable machine learning framework to predict measures of CAD severity and identify cell types driving the predictions. AI-ready data will be shared and serve as a model of how to prepare patient single cell data to be AI-ready for precision medicine and other applications.