Subject classification obtained by cluster analysis and principal component analysis applied to flow cytometric data
Open accessAbstract
Background: Polychromatic flow cytometry (PFC) allows the simultaneous determination of multiple antigens in the same cell, resulting in the generation of a high number of subsets. As a consequence, data analysis is the main difficulty with this technology. Here we show the use of cluster analysis (CA) and principal component analyses (PCA) to simplify multicolor data visualization and to allow subjects' classification. Methods: By eight‐colour cytofluorimetric analysis, we investigated the T cell compartment in donors of different age (young, middle‐aged, and centenarians). T cell subsets were identified by combining positive and negative expression of antigens. The resulting data set was organized into a matrix and subjected to CA and PCA. Results: CA clustered people of different ages on the basis of cytofluorimetric profile. PCA of the cellular subsets identified centenarians within a different cluster from young donors, while middle‐aged donors were scattered between these groups. These approaches identified T cell phenotypes that changed with increasing age. In young donors, memory T cell subsets tended to be CD127+ and CD95− whereas CD127−, CD95+ phenotypes were found at higher frequencies in people with advanced age. Conclusions: Our data suggest the use of bioinformatic approaches to analyze large data‐sets generated by PFC and to obtain the rapid identification of key populations that best characterize a group of subjects. © 2007 International Society for Analytical Cytology
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These T-cell changes are commonly reported in blood and can also extend to lymphoid tissues and organs such as spleen, lymph nodes, lung and gut in old subjects.
“These cellular changes are commonly reported in the circulation (i.e., the blood) [73], but can also be extended to lymphoid tissues and organs (e.g., spleen, lymph nodes, lung and gut) of old subjects [74].”
From Aging of the immune system: Focus on inflammation and vaccination (2016) · cites this paper as [73]
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- Authors
- Lugli, E., Pinti, M., Nasi, M., Troiano, L., Ferraresi, R., Mussi, C., Salvioli, G., Patsekin, V., Robinson, J. P., Durante, C., Cocchi, M., & Cossarizza, A.
- Affiliations
- University of Modena and Reggio Emilia (IT)
- Purdue University West Lafayette (US)
- Corresponding author
- Cossarizza, Andrea
- ORCID
- Venue
- Cytometry Part A
- Publisher
- Wiley
- Published
- 2007-03-12
- Volume
- 71A
- Issue
- 5
- Pages
- 334-344
- ISSN
- 1552-4922 (ISSN-L)
- 1552-4930
- OpenAlex
- W1992672611
- Cited by
- 105
- References
- 29
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 1 · 2023: 5 · 2022: 3 · 2021: 2 · 2020: 6 · 2019: 6 · 2018: 3 · 2017: 10 · 2016: 5 · 2015: 3 · 2014: 6 · 2013: 3 · 2012: 10
- FWCI
- 3.72
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cytometry Part A (publishedVersion)
- PubMed (publishedVersion)
- IRIS UNIMORE (University of Modena and Reggio Emilia) (submittedVersion, cc-by)
- INFM-OAR (INFN Catania) (submittedVersion, other-oa)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- polychromatic flow cytometry, T cell subsets, centenarians, memory T cells, CD127, Fas, subject classification, clustering, principal component analysis
- MeSH terms
- Adult, Aged, 80 and over, Aging, Classification, Female, Flow Cytometry, Humans, Immunologic Memory, Male, Middle Aged, CD4-Positive T-Lymphocytes, Cluster Analysis, CD8-Positive T-Lymphocytes, fas Receptor, Principal Component Analysis, ADP-ribosyl Cyclase 1, Interleukin-7 Receptor alpha Subunit
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