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Updated: Feb 28, 2026

Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis
Published on: October 17, 2018
Human Blood Monocyte Subsets: A New Gating Strategy Defined Using Cell Surface Markers Identified by Mass Cytometry
Graham D Thomas1, Anouk A J Hamers2, Catherine Nakao2
1From the Division of Inflammation Biology, La Jolla Institute for Allergy and Immunology, CA (G.D.T., A.A.J.H., C.N., P.M., C.C.H.); and Division of Cardiology and Robert M. Berne Cardiovascular Center, University of Virginia, Charlottesville (A.M.T., C.M., A.T.N., C.A.M.). gthomas@coipharma.com hedrick@lji.org.
Insights
Researchers developed a new gating strategy to accurately identify human monocyte subsets using mass cytometry. This improved method enhances the purity of intermediate and nonclassical monocytes, crucial for understanding cardiovascular disease.
Area of Science:
- Immunology
- Hematology
- Cardiovascular Research
Background:
- Human monocytes are classified into classical (CD14++CD16-), intermediate (CD14++CD16+), and nonclassical (CD14+CD16+) subsets.
- Monocyte subset alterations are linked to clinical outcomes, particularly cardiovascular disease, where intermediate monocytes predict events.
- Current methods for defining monocyte subsets yield inconsistent results, hindering mechanistic studies.
Purpose of the Study:
- To develop a more accurate method for identifying and purifying human monocyte subsets.
- To improve the reliability of monocyte subset analysis in the context of cardiovascular disease research.
Main Methods:
- Utilized cytometry by time-of-flight mass cytometry with 36 cell surface markers.
- Employed viSNE (visual interactive stochastic neighbor embedding) for high-dimensional analysis of monocyte populations.
- Developed and validated a revised gating scheme incorporating CCR2, CD36, HLA-DR, and CD11c markers.
Main Results:
- Standard CD14 and CD16 gating results in significant contamination of intermediate (≈86.0%) and nonclassical (≈87.2%) monocyte subsets.
- The novel gating scheme, using additional markers, increased intermediate and nonclassical monocyte purity to 98.8% and 99.1%, respectively.
- Demonstrated the applicability of the revised gating scheme using conventional flow cytometry in patients with cardiovascular disease.
Conclusions:
- A refined panel of surface markers and a new gating strategy significantly enhance monocyte subset identification and purity.
- This improved method is crucial for accurate monocyte function studies in clinical settings, especially for cardiovascular disease.
- The findings provide a more robust approach for immunological research involving human monocyte subsets.
Objective:
Human monocyte subsets are defined as classical (CD14++CD16-), intermediate (CD14++CD16+), and nonclassical (CD14+CD16+). Alterations in monocyte subset frequencies are associated with clinical outcomes, including cardiovascular disease, in which circulating intermediate monocytes independently predict cardiovascular events. However, delineating mechanisms of monocyte function is hampered by inconsistent results among studies.
Approach And Results:
We use cytometry by time-of-flight mass cytometry to profile human monocytes using a panel of 36 cell surface markers. Using the dimensionality reduction approach visual interactive stochastic neighbor embedding (viSNE), we define monocytes by incorporating all cell surface markers simultaneously. Using viSNE, we find that although classical monocytes are defined with high purity using CD14 and CD16, intermediate and nonclassical monocytes defined using CD14 and CD16 alone are frequently contaminated, with average intermediate and nonclassical monocyte purity of ≈86.0% and 87.2%, respectively. To improve the monocyte purity, we devised a new gating scheme that takes advantage of the shared coexpression of cell surface markers on each subset. In addition to CD14 and CD16, CCR2, CD36, HLA-DR, and CD11c are the most informative markers that discriminate among the 3 monocyte populations. Using these additional markers as filters, our revised gating scheme increases the purity of both intermediate and nonclassical monocyte subsets to 98.8% and 99.1%, respectively. We demonstrate the use of this new gating scheme using conventional flow cytometry of peripheral blood mononuclear cells from subjects with cardiovascular disease.
Conclusions:
Using cytometry by time-of-flight mass cytometry, we have identified a small panel of surface markers that can significantly improve monocyte subset identification and purity in flow cytometry. Such a revised gating scheme will be useful for clinical studies of monocyte function in human cardiovascular disease.
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