Abstract
Inflammation is a biological phenomenon beneficial for homeostasis, but it is unfavorable if dysregulated. Although major progress has been made in characterizing inflammation in specific diseases, a global, holistic understanding is still elusive. This is particularly intriguing, considering its function for human health and the potential for modern medicine if fully deciphered. In this study, we leveraged advances in single-cell transcriptomics to delineate inflammatory processes of circulating immune cells during infection, immune-mediated inflammatory diseases and cancer. Our single-cell atlas of more than 6.5 million peripheral blood mononuclear cells from 1,047 patients (56% female, 43% male) and 19 diseases allowed us to learn a comprehensive model of inflammation in circulating immune cells. The atlas expands current knowledge of the biology of inflammation of immune-mediated diseases, acute and chronic inflammatory diseases, infections and solid tumors and lays the foundation to develop a disease classification framework using unsupervised as well as explainable machine learning. Beyond a disease-centered analysis, we charted altered activity of inflammatory molecules in peripheral blood cells, depicting discriminative inflammation-related genes to further understand mechanisms of inflammation. We present a rich resource for the community and lay the groundwork for learning a classifier for inflammatory diseases, presenting cells in circulation as living biomarkers.