Establishment of normative ranges of the healthy human immune system with comprehensive polychromatic flow cytometry profiling.
Abstract
Existing normative flow cytometry data have several limitations including small sample
sizes, incompletely described study populations, variable flow cytometry methodology,
and limited depth for defining lymphocyte subpopulations. To overcome these issues,
we defined high-dimensional flow cytometry reference ranges for the healthy human
immune system using Human Immunology Project Consortium methodologies after carefully
screening 127 subjects deemed healthy through clinical and laboratory testing. We
enrolled subjects in the following age cohorts: 18-29 years, 30-39, 40-49, and 50-66
and enrolled cohorts to ensure an even gender distribution and at least 30% non-Caucasians.
From peripheral blood mononuclear cells, flow cytometry reference ranges were defined
for >50 immune subsets including T-cell (activation, maturation, T follicular helper
and regulatory T cell), B-cell, and innate cells. We also developed a web tool for
visualization of the dataset and download of raw data. This dataset provides the immunology
community with a resource to compare and extract data from rigorously characterized
healthy subjects across age groups, gender and race.
Type
Journal articleSubject
Leukocytes, MononuclearLymphocyte Subsets
Humans
Flow Cytometry
Cell Separation
Age Factors
Immunity, Cellular
Reference Values
Adolescent
Adult
Aged
Middle Aged
Continental Population Groups
Female
Male
Young Adult
Healthy Volunteers
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https://hdl.handle.net/10161/21778Published Version (Please cite this version)
10.1371/journal.pone.0225512Publication Info
Yi, John S; Rosa-Bray, Marilyn; Staats, Janet; Zakroysky, Pearl; Chan, Cliburn; Russo,
Melissa A; ... Guptill, Jeffrey T (2019). Establishment of normative ranges of the healthy human immune system with comprehensive
polychromatic flow cytometry profiling. PloS one, 14(12). pp. e0225512. 10.1371/journal.pone.0225512. Retrieved from https://hdl.handle.net/10161/21778.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Chi Wei Cliburn Chan
Professor of Biostatistics & Bioinformatics
Computational immunology (stochastic and spatial models and simulations, T cell signaling,
immune regulation) Statistical methodology for immunological laboratory techniques
(flow cytometry, CFSE analysis, receptor-ligand binding and signaling kinetics) Informatics
of the immune system (reference and application ontologies, meta-programming, text
mining and machine learning)
Jeffrey Guptill
Adjunct Associate Professor in the Department of Neurology
Kent James Weinhold
Joseph W. and Dorothy W. Beard Distinguished Professor of Experimental Surgery
The Weinhold Laboratory is currently focused on utilizing a comprehensive repertoire
of highly standardized and formerly validated assay platforms to profile the human
immune system in order to identify immunologic signatures that predict disease outcomes.
These ongoing studies span a broad range of highly relevant clinical arenas, including:
1) cancer (non-small cell lung cancer, head and neck cancer, glioblastoma neoforme,
ovarian cancer, and prostate cancer), 2) autoimmune
John S Yi
Adjunct Assistant Professor in the Department of Surgery
I am an immunologist, with a focus to characterize the immune system in response to
infectious and non-infectious diseases including cancer, HIV, autoimmune disease,
and transplantation. My goals are to identify novel biomarkers/immune signatures that
clinicians can utilize to diagnosis, predict disease outcomes, and determine patients'
response to treatment.
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