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COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity

Here we consider how high‐content flow cytometric methodology at appropriate scale and throughput rapidly provided meaningful biological data in our recent studies of COVID‐19, which we discuss in the context of other similar investigations. In our work, high‐throughput flow cytometry was instrument...

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Autores principales: del Molino del Barrio, Irene, Hayday, Thomas S., Laing, Adam G., Hayday, Adrian C., Di Rosa, Francesca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9011838/
https://www.ncbi.nlm.nih.gov/pubmed/34811890
http://dx.doi.org/10.1002/cyto.a.24516
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author del Molino del Barrio, Irene
Hayday, Thomas S.
Laing, Adam G.
Hayday, Adrian C.
Di Rosa, Francesca
author_facet del Molino del Barrio, Irene
Hayday, Thomas S.
Laing, Adam G.
Hayday, Adrian C.
Di Rosa, Francesca
author_sort del Molino del Barrio, Irene
collection PubMed
description Here we consider how high‐content flow cytometric methodology at appropriate scale and throughput rapidly provided meaningful biological data in our recent studies of COVID‐19, which we discuss in the context of other similar investigations. In our work, high‐throughput flow cytometry was instrumental to identify a consensus immune signature in COVID‐19 patients, and to investigate the impact of SARS‐CoV‐2 exposure on patients with either solid or hematological cancers. We provide here some examples of our ‘holistic’ approach, in which flow cytometry data generated by lymphocyte and myelomonocyte panels were integrated with other analytical metrics, including SARS‐CoV‐2‐specific serum antibody titers, plasma cytokine/chemokine levels, and in‐depth clinical annotation. We report how selective differences between T cell subsets were revealed by a newly described flow cytometric T(DS) assay to distinguish actively cycling T cells in the peripheral blood. By such approaches, our and others' high‐content flow cytometry studies collectively identified overt abnormalities and subtle but critical changes that discriminate the immuno‐signature of COVID‐19 patients from those of healthy donors and patients with non‐COVID respiratory infections. Thereby, these studies offered several meaningful biomarkers of COVID‐19 severity that have the potential to improve the management of patients and of hospital resources. In sum, flow cytometry provides an important means for rapidly obtaining data that can guide clinical decision‐making without requiring highly expensive, sophisticated equipment, and/or “‐omics” capabilities. We consider how this approach might be further developed.
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spelling pubmed-90118382022-04-15 COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity del Molino del Barrio, Irene Hayday, Thomas S. Laing, Adam G. Hayday, Adrian C. Di Rosa, Francesca Cytometry A Review Articles Here we consider how high‐content flow cytometric methodology at appropriate scale and throughput rapidly provided meaningful biological data in our recent studies of COVID‐19, which we discuss in the context of other similar investigations. In our work, high‐throughput flow cytometry was instrumental to identify a consensus immune signature in COVID‐19 patients, and to investigate the impact of SARS‐CoV‐2 exposure on patients with either solid or hematological cancers. We provide here some examples of our ‘holistic’ approach, in which flow cytometry data generated by lymphocyte and myelomonocyte panels were integrated with other analytical metrics, including SARS‐CoV‐2‐specific serum antibody titers, plasma cytokine/chemokine levels, and in‐depth clinical annotation. We report how selective differences between T cell subsets were revealed by a newly described flow cytometric T(DS) assay to distinguish actively cycling T cells in the peripheral blood. By such approaches, our and others' high‐content flow cytometry studies collectively identified overt abnormalities and subtle but critical changes that discriminate the immuno‐signature of COVID‐19 patients from those of healthy donors and patients with non‐COVID respiratory infections. Thereby, these studies offered several meaningful biomarkers of COVID‐19 severity that have the potential to improve the management of patients and of hospital resources. In sum, flow cytometry provides an important means for rapidly obtaining data that can guide clinical decision‐making without requiring highly expensive, sophisticated equipment, and/or “‐omics” capabilities. We consider how this approach might be further developed. John Wiley & Sons, Inc. 2021-11-22 /pmc/articles/PMC9011838/ /pubmed/34811890 http://dx.doi.org/10.1002/cyto.a.24516 Text en © 2021 The Authors. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Review Articles
del Molino del Barrio, Irene
Hayday, Thomas S.
Laing, Adam G.
Hayday, Adrian C.
Di Rosa, Francesca
COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity
title COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity
title_full COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity
title_fullStr COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity
title_full_unstemmed COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity
title_short COVID‐19: Using high‐throughput flow cytometry to dissect clinical heterogeneity
title_sort covid‐19: using high‐throughput flow cytometry to dissect clinical heterogeneity
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9011838/
https://www.ncbi.nlm.nih.gov/pubmed/34811890
http://dx.doi.org/10.1002/cyto.a.24516
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