Evaluating Cellular Polyfunctionality with a Novel Polyfunctionality Index

• Published in: PloS one Vol. 7; no. 7; p. e42403
• Main Authors: Larsen, Martin, Sauce, Delphine, Arnaud, Laurent, Fastenackels, Solène, Appay, Victor, Gorochov, Guy
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 30.07.2012; Public Library of Science (PLoS)
• Subjects: Analysis; Animals; Arthritis; Biology; Charts; Chemokines; Cluster analysis; Combinatorial analysis; Cytokines; Cytometry; Data analysis; Datasets; Demand analysis; Flow Cytometry; HIV; Human immunodeficiency virus; Humans; Immunology; Interferon; Life Sciences; Lymphocytes; Lymphocytes T; Medicine; Monkeys; Species Specificity; Statistical analysis; Statistical tests; Studies; T cell receptors; T cells; T-Lymphocytes - cytology; Vaccination; γ-Interferon; France
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0042403

Functional evaluation of naturally occurring or vaccination-induced T cell responses in mice, men and monkeys has in recent years advanced from single-parameter (e.g. IFN-γ-secretion) to much more complex multidimensional measurements. Co-secretion of multiple functional molecules (such as cytokines and chemokines) at the single-cell level is now measurable due primarily to major advances in multiparametric flow cytometry. The very extensive and complex datasets generated by this technology raise the demand for proper analytical tools that enable the analysis of combinatorial functional properties of T cells, hence polyfunctionality. Presently, multidimensional functional measures are analysed either by evaluating all combinations of parameters individually or by summing frequencies of combinations that include the same number of simultaneous functions. Often these evaluations are visualized as pie charts. Whereas pie charts effectively represent and compare average polyfunctionality profiles of particular T cell subsets or patient groups, they do not document the degree or variation of polyfunctionality within a group nor does it allow more sophisticated statistical analysis. Here we propose a novel polyfunctionality index that numerically evaluates the degree and variation of polyfuntionality, and enable comparative and correlative parametric and non-parametric statistical tests. Moreover, it allows the usage of more advanced statistical approaches, such as cluster analysis. We believe that the polyfunctionality index will render polyfunctionality an appropriate end-point measure in future studies of T cell responsiveness.