Save
Naïve T-cell homeostasis differs between patients with two subtypes of multiple sclerosis
Author(s): ,
D. Haegert
Affiliations:
Pathology, McGill University
,
Y. Lapierre
Affiliations:
Neurology, Montreal Neurological Institute, McGill University
,
J. Antel
Affiliations:
Neuroimmunology Unit, Department of Neurology, McGill University, Montreal, QC, Canada
,
A. Bar-Or
Affiliations:
Center for Neuroinflammation and Experimental Therapeutics and the Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
L. Fitz-Gerald
Affiliations:
Pathology, McGill University
ECTRIMS Online Library. Haegert D. Oct 12, 2018; 228917
David Haegert
David Haegert
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Abstract
Discussion Forum (0)
Rate & Comment (0)

Abstract: P1076

Type: Poster Sessions

Abstract Category: Pathology and pathogenesis of MS - Immunology

Background: T-cell homeostasis balances thymic output, homeostatic proliferation and T-cell loss. Altered T-cell homeostasis may predispose to autoimmune disease. Some report reduced thymic output in patients with multiple sclerosis (MS), but evidence of altered homeostatic proliferation is controversial and no relevant data are available on T-cell loss. Here, we questioned whether patients with relapsing-remitting MS (RRMS) and primary progressive MS (PPMS) show differences in naïve CD4 T-cell homeostasis.
Methods: We used mathematical modeling, based partly on quantitative T-cell receptor excision circle (TREC) data, to compare daily thymic export (σ) and proliferation (p) and the rate of daily T-cell loss (d) in healthy controls (HCs) (n=12), and patients with RRMS (n=22) and PPMS (n=17), with mean ages of 45, 46 and 48. We derived d from one mathematical model of σ: σ=yNC÷Δ(c-C); y is the T-cell fraction expressing Ki-67, N is the number of T-cells/ml of peripheral blood, Δ is the duration of Ki-67 expression, c is the average TREC content of CD4 recent thymic emigrants, C is naïve CD4 TREC content, and d=(σc/C-dN/dt) ÷N. We incorporated estimates of d into a second mathematical model, and then calculated daily σ and p: σ=NdC/c and p=σ(c-C)/C.
Results: Mean naïve CD4 T-cell numbers did not differ between HCs and patients with RRMS and PPMS (4.6, 3.9 and 4.4 X 105 T-cells/ml) and were constant with age (r=-0.26, -0.02 and 0.29). Daily p exceeded daily σ in HCs (medians, 136.1 vs. 9.6 T-cells/ml, P=0.002), and in patients with RRMS (93.2 vs. 2.5 T-cells/ml, P< 0.0001) and PPMS (167.3 vs. 1.65 T-cells/ml,
P=0.008). Median daily p/ml and d did not differ between the groups. Daily σ/ml was lower in patients with PPMS than in HCs (P=0.01). Daily σ/ml (r =-0.48, P=0.044), daily p/ml
(r =-0.487, P=0.047) and d (r =-0.565, P=0.024) decreased with age only in patients with RRMS.
Conclusions: Proliferation was the main contributor to naïve CD4 T-cells in all groups. Patients with PPMS had reduced daily thymic export but the magnitude of daily proliferation was sufficient to maintain normal naïve CD4 T-cell numbers. In patients with RRMS, the findings suggest that reduced T-cell loss with age maintained naïve CD4 T-cell numbers in spite of declining thymic export and proliferation. In summary, the contributions to naïve T-cell homeostasis differ not only between HCs and the patient groups but also between the patient groups.
Disclosure: This work was supported in part by a grant from the Multiple Sclerosis Society of Canada.
Dr. David Haegert has received grants from Novartis and Sanofi-Genzyme.
Dr. Y. Lapierre has received consulting fees and serves on advisory boards from Biogen Idec, Bayer, EMD Serono, Genzyme, Novartis, Teva.
Dr, Jack Antel serves on advisory/safety monitoring boards for Novartis, Sanofi-Genzyme, Biogen Idec, EMD Serono and Medday Pharmaceuticals and is editor of the Americas, Multiple Sclerosis Journal.
Amit Bar-Or participated as a speaker in meetings sponsored by and received consulting fees and/or grant support from: Atara Biotherapeutics, Biogen Idec, Celgene/Receptos, Genentech/Roche, GlaxoSmithKline, MAPI, Medimmune, Merck/EMD Serono, Novartis, Sanofi-Genzyme.
Leslie Fitz-Gerald has no disclosures.

Code of conduct/disclaimer available in General Terms & Conditions
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.


Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.



Google Analytics is used for user behavior tracking/reporting. Google Analytics works in parallel and independently from MLG’s features. Google Analytics relies on cookies and these cookies can be used by Google to track users across different platforms/services.


Save Settings