Human Monocytes - CD14, CD16 - Ziegler-Heitbrock

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Single cell RNA sequencing reveals profound changes in circulating immune cells in patients with heart failure.

Abstract

AIMS: Identification of signatures of immune cells at single cell level may provide novel insights into changes of immune related disorders. Therefore, we used single cell RNA sequencing to determine the impact of heart failure on circulating immune cells. METHODS AND RESULTS: We demonstrate a significant change in monocyte to T cell ratio in patients with heart failure, compared to healthy subjects, which were validated by flow cytometry analysis. Subclustering of monocytes and stratification of the clusters according to relative CD14 and FCGR3A (CD16) expression allowed annotation of classical, intermediate and non-classical monocytes. Heart failure had a specific impact on the gene expression patterns in these subpopulations. Metabolically active genes such as FABP5 were highly enriched in classical monocytes of heart failure patients, whereas beta-catenin expression was significantly higher in intermediate monocytes. The selective regulation of signatures in the monocyte subpopulations was validated by classical and multifactor dimensionality reduction flow cytometry analyses. CONCLUSION: Together this study shows that circulating cells derived from patients with heart failure have altered phenotypes. These data provide a rich source for identification of signatures of immune cells in heart failure compared to healthy subjects. The observed increase in FABP5 and signatures of Wnt signaling may contribute to enhanced monocyte activation. TRANSLATIONAL PERSPECTIVE: This study is the first to identify the impact of chronic ischemic heart disease on monocyte signatures at a single cell level. The study demonstrates profound changes in the transcriptome of monocytes which can be recapitulated in multidimensional flow cytometry analysis. The bioinformatic assessment of monocyte signatures provides the basis for future studies assessing the impact of single cell analysis as prognostic tool or for guiding anti-inflammatory therapies associated with cardiovascular disease.

Authors: Abplanalp WT, John D, Cremer S, Assmus B, Dorsheimer L, Hoffmann J, Becker-Pergola G, Rieger MA, Zeiher AM, Vasa-Nicotera M, Dimmeler S,
Journal: Cardiovasc. Res.; 2020 Apr 20 . doi:10.1093/cvr/cvaa101
Year: 2020
PubMed: PMID: 32311026 (Go to PubMed)