The immune response to antigen is characterized by an initial activation followed by the development of effector mechanisms, such as the delayed-type hypersensitivity (DTH) in the murine system, and can be distinguished on the basis of lymphokine secretion. The Thl cells secrete IL-2, IFN-gamma and lymphotoxin and provide help for the DTH response whereas Th2 cells secrete IL-4, IL-5, IL-6 and IL-l0 and provide help for antigen-specific antibody responses. In vitro studies have revealed that the interactions occurring between these cells can be either antagonistic or synergistic. In vivo, the balance between these two subsets is tightly regulated, but when this regulation is not maintained, one subset may predominate over the other. This may be occurring in such diseases as asthma or systemic lupus erythematosus in which the Th2 cells have been shown to dominate.
The specific aims of this proposal are to use the mathematical tools of dynamic modeling to study the interactions between Thl, Th2 cells and the lymphokines they secrete. A model will be developed on the basis of available data. This model will be refined and precised using Thl and Th2 clones available in the laboratory. The model will then be analyzed for its dynamical content using a computer program. This involves allowing the variables to evolve over time, and points of equilibrium will be identified. These equilibria will correspond to normal states of balance between the two types of cells as well as abnormal states, reflecting certain disease states. An in vitro system will be developed to test the predictions of the model. This system will involve the use of a panel of antigen-specific T cell clones, some of which are Thl and others are Th2. These clones can be activated using the same antigenic stimuli. It will be possible, therefore, to carry out experiments in which Thl and Th2 clones of the same specificity are mixed, activated simultaneously, and the pattern of lymphokine secretion observed. It is anticipated that this approach will greatly increase their understanding of how these two cell types might interact in vivo, and ultimately could lead to possible therapeutic manipulations in diseases characterized by an imbalance between these two important T cell subsets.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI031427-03
Application #
3146440
Study Section
Special Emphasis Panel (SSS (E))
Project Start
1991-08-01
Project End
1994-07-31
Budget Start
1993-08-01
Budget End
1994-07-31
Support Year
3
Fiscal Year
1993
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Type
Schools of Medicine
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
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Morel, Penelope A; Falkner, Dewayne; Plowey, Jeffrey et al. (2004) DNA immunisation: altering the cellular localisation of expressed protein and the immunisation route allows manipulation of the immune response. Vaccine 22:447-56
Oriss, T B; McCarthy, S A; Campana, M A et al. (1999) Evidence of positive cross-regulation on Th1 by Th2 and antigen-presenting cells: effects on Th1 induced by IL-4 and IL-12. J Immunol 162:1999-2007
Morel, P A; Oriss, T B (1998) Crossregulation between Th1 and Th2 cells. Crit Rev Immunol 18:275-303
Morel, P A (1998) Mathematical modeling of immunological reactions. Front Biosci 3:d338-7
Burke, M A; Morel, B F; Oriss, T B et al. (1997) Modeling the proliferative response of T cells to IL-2 and IL-4. Cell Immunol 178:42-52
Oriss, T B; McCarthy, S A; Morel, B F et al. (1997) Crossregulation between T helper cell (Th)1 and Th2: inhibition of Th2 proliferation by IFN-gamma involves interference with IL-1. J Immunol 158:3666-72
Morel, B F; Burke, M A; Kalagnanam, J et al. (1996) Making sense of the combined effect of interleukin-2 and interleukin-4 on lymphocytes using a mathematical model. Bull Math Biol 58:569-94
Lu, L; Hsieh, M; Oriss, T B et al. (1995) Generation of DC from mouse spleen cell cultures in response to GM-CSF: immunophenotypic and functional analyses. Immunology 84:127-34