Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 110, Issue 47, Pages 19030-19035Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1318322110
Keywords
automated analysis; flow cytometry
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Funding
- IDEA2 program at the Massachusetts Institute of Technology
- American Academy of Allergy, Asthma & Immunology ARTrust
- National Institutes of Health [AI063428, AI028973, DK057521, 5K08AR055688, U01HG0070033]
- American Diabetes Association [7-12-IN-07]
- Arthritis Foundation
- Harvard University Milton Foundation
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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, userguided 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.
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