Literature DB >> 19734223

Quantifying thymic export: combining models of naive T cell proliferation and TCR excision circle dynamics gives an explicit measure of thymic output.

Iren Bains1, Rodolphe Thiébaut, Andrew J Yates, Robin Callard.   

Abstract

Understanding T cell homeostasis requires knowledge of the export rate of new T cells from the thymus, a rate that has been surprisingly difficult to estimate. TCR excision circle (TREC) content has been used as a proxy for thymic export, but this quantity is influenced by cell division and loss of naive T cells and is not a direct measure of thymic export. We present in this study a method for quantifying thymic export in humans by combining two simple mathematical models. One uses Ki67 data to calculate the rate of peripheral naive T cell production, whereas the other tracks the dynamics of TRECs. Combining these models allows the contributions of the thymus and cell division to the daily production rate of T cells to be disentangled. The method is illustrated with published data on Ki67 expression and TRECs within naive CD4+ T cells in healthy individuals. We obtain a quantitative estimate for thymic export as a function of age from birth to 20 years. The export rate of T cells from the thymus follows three distinct phases, as follows: an increase from birth to a peak at 1 year, followed by rapid involution until approximately 8 years, and then a more gradual decline until 20 years. The rate of involution shown by our model is compatible with independent estimates of thymic function predicted by thymic epithelial space. Our method allows nonintrusive estimation of thymic output on an individual basis and may provide a means of assessing the role of the thymus in diseases such as HIV.

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Year:  2009        PMID: 19734223     DOI: 10.4049/jimmunol.0900743

Source DB:  PubMed          Journal:  J Immunol        ISSN: 0022-1767            Impact factor:   5.422


  55 in total

1.  Neonatal thymectomy reveals differentiation and plasticity within human naive T cells.

Authors:  Theo van den Broek; Eveline M Delemarre; Willemijn J M Janssen; Rutger A J Nievelstein; Jasper C Broen; Kiki Tesselaar; Jose A M Borghans; Edward E S Nieuwenhuis; Berent J Prakken; Michal Mokry; Nicolaas J G Jansen; Femke van Wijk
Journal:  J Clin Invest       Date:  2016-02-22       Impact factor: 14.808

2.  Effect of age on immunological response in the first year of antiretroviral therapy in HIV-1-infected adults in West Africa.

Authors:  Eric Balestre; Serge P Eholié; Amani Lokossue; Papa Salif Sow; Man Charurat; Albert Minga; Joseph Drabo; François Dabis; Didier K Ekouevi; Rodolphe Thiébaut
Journal:  AIDS       Date:  2012-05-15       Impact factor: 4.177

Review 3.  A population biological approach to understanding the maintenance and loss of the T-cell repertoire during aging.

Authors:  Philip L F Johnson; Jörg J Goronzy; Rustom Antia
Journal:  Immunology       Date:  2014-06       Impact factor: 7.397

Review 4.  Thymic stromal cells: Roles in atrophy and age-associated dysfunction of the thymus.

Authors:  Sergio Cepeda; Ann V Griffith
Journal:  Exp Gerontol       Date:  2017-12-24       Impact factor: 4.032

5.  A comparison of TRECs and flow cytometry for naive T cell quantification.

Authors:  S P Adams; S Kricke; E Ralph; N Gilmour; K C Gilmour
Journal:  Clin Exp Immunol       Date:  2017-10-27       Impact factor: 4.330

6.  Peripheral selection rather than thymic involution explains sudden contraction in naive CD4 T-cell diversity with age.

Authors:  Philip L F Johnson; Andrew J Yates; Jörg J Goronzy; Rustom Antia
Journal:  Proc Natl Acad Sci U S A       Date:  2012-12-10       Impact factor: 11.205

Review 7.  Emerging concepts in tissue-resident T cells: lessons from humans.

Authors:  Joseph J C Thome; Donna L Farber
Journal:  Trends Immunol       Date:  2015-06-10       Impact factor: 16.687

8.  Double negative (CD3+ 4- 8-) TCR alphabeta splenic cells from young NOD mice provide long-lasting protection against type 1 diabetes.

Authors:  Beverly Duncan; Cristina Nazarov-Stoica; Jacqueline Surls; Margaret Kehl; Constantin Bona; Sofia Casares; Teodor-D Brumeanu
Journal:  PLoS One       Date:  2010-07-02       Impact factor: 3.240

9.  Quantifying T lymphocyte turnover.

Authors:  Rob J De Boer; Alan S Perelson
Journal:  J Theor Biol       Date:  2013-01-09       Impact factor: 2.691

10.  Bayesian immunological model development from the literature: example investigation of recent thymic emigrants.

Authors:  Tyson H Holmes; David B Lewis
Journal:  J Immunol Methods       Date:  2014-08-29       Impact factor: 2.303

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