title: Application of user-guided automated cytometric data analysis to large-scale immunoprofiling of invariant natural killer T cells.
abstract: Defining and characterizing pathologies of the immune system requires precise and accurate quantification of abundances and functions of cellular subsets via cytometric studies. At this time, data analysis relies on manual gating, which is a major source of variability in large-scale studies. We devised an automated, user-guided method, X-Cyt, which specializes in rapidly and robustly identifying targeted populations of interest in large data sets. We first applied X-Cyt to quantify CD4(+) effector and central memory T cells in 236 samples, demonstrating high concordance with manual analysis (r = 0.91 and 0.95, respectively) and superior performance to other available methods. We then quantified the rare mucosal associated invariant T cell population in 35 samples, achieving manual concordance of 0.98. Finally we characterized the population dynamics of invariant natural killer T (iNKT) cells, a particularly rare peripheral lymphocyte, in 110 individuals by assaying 19 markers. We demonstrated that although iNKT cell numbers and marker expression are highly variable in the population, iNKT abundance correlates with sex and age, and the expression of phenotypic and functional markers correlates closely with CD4 expression.
authors.affiliation: Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115.
authors.forename: Xinli
authors.initials: X
authors.lastname: Hu
authors.forename: Hyun
authors.initials: H
authors.lastname: Kim
authors.forename: Patrick J
authors.initials: PJ
authors.lastname: Brennan
authors.forename: Buhm
authors.initials: B
authors.lastname: Han
authors.forename: Clare M
authors.initials: CM
authors.lastname: Baecher-Allan
authors.forename: Philip L
authors.initials: PL
authors.lastname: De Jager
authors.forename: Michael B
authors.initials: MB
authors.lastname: Brenner
authors.forename: Soumya
authors.initials: S
authors.lastname: Raychaudhuri
mesh_terms: D000367:Age Factors; D015415:Biomarkers / Q000032:analysis*; D015704:CD4 Antigens / Q000378:metabolism; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D055611:Natural Killer T-Cells / Q000166:cytology* / Q000276:immunology*; D012737:Sex Factors; D012984:Software
chemical_list: D015415:Biomarkers; D015704:CD4 Antigens
keywords: automated analysis; flow cytometry