Literature DB >> 12884307

Measurement and modeling of human T cell kinetics.

Derek C Macallan1, Becca Asquith, Andrew J Irvine, Diana L Wallace, Andrew Worth, Hala Ghattas, Yan Zhang, George E Griffin, David F Tough, Peter C Beverley.   

Abstract

The ability to measure, describe and interpret T cell kinetics is pivotal in understanding normal lymphocyte homeostasis and diseases that affect T cell numbers. Following in vivo labeling of dividing cells with 6,6-D(2)-glucose in eight healthy volunteers, peripheral blood T cells were sorted by CD4, CD8 and CD45 phenotype. Enrichment of deuterium in DNA was measured by gas chromatography-mass spectrometry. A novel model of T cell kinetics, allowing for heterogeneity within T cell pools, was used to analyze data on acquisition and loss of label and calculate proliferation and disappearance rates for each subpopulation. Proliferation rates for CD45RO(+)CD8(+) cells and CD45RO(+)CD4(+) cells were 5.1% and 2.7% /day, respectively (equivalent doubling times: 14 and 26 days). CD45RA(+)CD8(+) lymphocytes and CD45RA(+)CD4(+) lymphocytes had slower proliferation rates, 0.5% and 0.6% / day, respectively (doubling time about 4 months). Disappearance rates of labeled cells were similar for all cell types (7%-12% / day) and exceeded corresponding proliferation rates. This disparity may be understood conceptually in terms of either phenotypic heterogeneity (rapid versus slow turnover pools), or history (recently divided cells are more likely to die). The new kinetic model fits the data closely and avoids the need to postulate a large external source of lymphocytes to maintain equilibrium.

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Year:  2003        PMID: 12884307     DOI: 10.1002/eji.200323763

Source DB:  PubMed          Journal:  Eur J Immunol        ISSN: 0014-2980            Impact factor:   5.532


  47 in total

1.  Modelling deuterium labelling of lymphocytes with temporal and/or kinetic heterogeneity.

Authors:  Rob J De Boer; Alan S Perelson; Ruy M Ribeiro
Journal:  J R Soc Interface       Date:  2012-04-18       Impact factor: 4.118

Review 2.  Immunology and mathematics: crossing the divide.

Authors:  Robin E Callard; Andrew J Yates
Journal:  Immunology       Date:  2005-05       Impact factor: 7.397

Review 3.  Aging and T-cell diversity.

Authors:  Jörg J Goronzy; Won-Woo Lee; Cornelia M Weyand
Journal:  Exp Gerontol       Date:  2007-01-10       Impact factor: 4.032

4.  Memory T and memory B cells share a transcriptional program of self-renewal with long-term hematopoietic stem cells.

Authors:  Chance John Luckey; Deepta Bhattacharya; Ananda W Goldrath; Irving L Weissman; Christophe Benoist; Diane Mathis
Journal:  Proc Natl Acad Sci U S A       Date:  2006-02-21       Impact factor: 11.205

5.  In-vivo assessment of T cell kinetics in individuals at risk for type 1 diabetes.

Authors:  W Hao; H T Bahnson; C Speake; K Cerosaletti; C J Greenbaum
Journal:  Clin Exp Immunol       Date:  2019-10-07       Impact factor: 4.330

6.  A mechanistic model for bromodeoxyuridine dilution naturally explains labelling data of self-renewing T cell populations.

Authors:  Vitaly V Ganusov; Rob J De Boer
Journal:  J R Soc Interface       Date:  2012-11-08       Impact factor: 4.118

7.  Quantifying the development of the peripheral naive CD4+ T-cell pool in humans.

Authors:  Iren Bains; Rustom Antia; Robin Callard; Andrew J Yates
Journal:  Blood       Date:  2009-01-28       Impact factor: 22.113

Review 8.  Human T-lymphotropic virus type 1 (HTLV-1): persistence and immune control.

Authors:  Charles R M Bangham
Journal:  Int J Hematol       Date:  2003-11       Impact factor: 2.490

9.  Rapid turnover of effector-memory CD4(+) T cells in healthy humans.

Authors:  Derek C Macallan; Diana Wallace; Yan Zhang; Catherine De Lara; Andrew T Worth; Hala Ghattas; George E Griffin; Peter C L Beverley; David F Tough
Journal:  J Exp Med       Date:  2004-07-12       Impact factor: 14.307

10.  In vivo intraclonal and interclonal kinetic heterogeneity in B-cell chronic lymphocytic leukemia.

Authors:  Carlo Calissano; Rajendra N Damle; Gregory Hayes; Elizabeth J Murphy; Marc K Hellerstein; Carol Moreno; Cristina Sison; Matthew S Kaufman; Jonathan E Kolitz; Steven L Allen; Kanti R Rai; Nicholas Chiorazzi
Journal:  Blood       Date:  2009-09-29       Impact factor: 22.113

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