Abstract 439: High Dimensional Single-Cell Immune Contexture of Human Atherosclerotic Plaques and Blood
Atherosclerosis is a disease characterized by immune infiltration of the arterial wall in response to tissue damage and systemic inflammation. In the era of precision medicine, is essential to gain insights on immune contexture of atherosclerotic tissue taking into account disease-specific cell variation in patients. We applied high-dimensional technologies for the analysis of multiple parameters at the single-cell level in clinical samples of patients undergoing carotid endatherectomy (CEA, n=15). Using time-of-flight mass-cytometry (CyTOF), we simultaneously analyzed 32 parameters at the single-cell level in peripheral blood mononuclear cells (PBMCs) and atherosclerotic-tissue associated immune cells of the same patient. Using viSNE, we mapped single-cell heterogeneity into two dimensions to discriminate PBMCs and tissue-associated CD45+ immune cells. Next, we employed Phenograph to cluster cells into phenotypically related populations, which were annotated based on canonical marker expression patterns. We identified several major immune subsets including two subsets of macrophages (CD163 low and CD163 high ), monocytes, dendritic cells (DCs), B and T cells. The most prevalent CD45+ cells identified in atherosclerotic tissue were CD4 + (25.8%) and CD8 + (25.2%) T cells, macrophages (12.8%), monocytes (7.7%) and B (2.1%) cells. Using a regression analysis similar to that employed by CITRUS, we determined that macrophages and a subset of CD8 T cells characterized by low expression of CD127 were selectively enriched in tissue vs. blood. Multiplexed immunohistochemistry confirmed that T cells comprised a major portion of the CD45+ cells in atherosclerotic tissue, even more abundant than macrophages. This study of deep phenotyping across-atherosclerotic tissue and blood demonstrate a significant T cell tissue infiltration of a specific subset of CD8 T cells. This suggests that adaptive T cell immunity plays a critical role in advanced atherosclerosis. The extension of this systems biology analysis pipeline to larger datasets can improve our understanding of the core mechanisms of chronic inflammation in atherosclerosis.