Subject classification obtained by cluster analysis and principal component analysis applied to flow cytometric data.
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.
Lugli
Enrico
E
Department of Biomedical Sciences, Chair of Immunology, University of Modena and Reggio Emilia, via Campi 287, 41100 Modena, Italy.
Pinti
Marcello
M
Nasi
Milena
M
Troiano
Leonarda
L
Ferraresi
Roberta
R
Mussi
Chiara
C
Salvioli
Gianfranco
G
Patsekin
Valeri
V
Robinson
J Paul
JP
Durante
Caterina
C
Cocchi
Marina
M
Cossarizza
Andrea
A
D051997:ADP-ribosyl Cyclase 1 / Q000032:analysis; D000328:Adult; D000369:Aged, 80 and over; D000375:Aging / Q000276:immunology; D015496:CD4-Positive T-Lymphocytes / Q000166:cytology / Q000378:metabolism; D018414:CD8-Positive T-Lymphocytes / Q000166:cytology / Q000378:metabolism; D002965:Classification; D016000:Cluster Analysis; D005260:Female; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D007156:Immunologic Memory; D053699:Interleukin-7 Receptor alpha Subunit / Q000032:analysis; D008297:Male; D008875:Middle Aged; D025341:Principal Component Analysis; D019014:fas Receptor / Q000032:analysis
D053699:Interleukin-7 Receptor alpha Subunit; D019014:fas Receptor; D051997:ADP-ribosyl Cyclase 1