MODELING CELLULAR IMMUNITY DURING HIV AND TB INFECTIONS

本提案的目的是解释th1型和TH2-的作用

The goal of this proposal is to explain the role of TH1-type and TH2- type cytokine profiles in disease progression for the pathogens human immunodeficiency virus type 1 (HIV-1) and Mycobacterium tuberculosis. We investigate the following hypotheses: (1) The progression of disease during the pathogenesis of HIV infection is dependent upon a long-term shift of TH1- and TH2-type cytokines that are expressed during the evolution of the disease. This paradigm would predict that a dominant phenotype characterized by TH2-type cytokines is present in end-stage disease. (2) The establishment and maintenance of latency in infection with Mycobacterium tuberculosis may be predicted based on the cytokine profiles, balancing the tissue damaging response with resolution. The three specific aims are to formulate mathematical models based on the complex cytokine network in the cellular immune response to disease to: (1) Determine the predictive role of a TH1/TH2 cytokine balance in differentiating the disease outcomes in infection with Mycobacterium tuberculosis. Specifically, we will investigate why most individuals develop latent TB infection, yet others progress to disease, via either a fast or slow progression. (2) Explore the role of a long-term TH1/TH2 cytokine shift expressed during HIV-1 disease progression and to determine the predictive role of a TH1/TH2 cytokine imbalance in that progression. (3) Investigate the use of cytokines as therapeutic strategies as agents of immunotherapy, either alone or in conjunction with chemotherapy, for both latent and progressive disease for both drug-resistant and drug-sensitive HIV-1 and M. tuberculosis. These results are also expected to lead to a greater understanding of co- infections with HIV-1 and TB. Mathematical models will be developed that reflect the dynamics of the different diseases as well as disease states. These models include experimental data and will be analyzed using mathematical approaches for characterizing nonlinear dynamical systems. The interaction of multiple factors that control, activate or facilitate the cellular-immune response to the pathogens will be defined. Key parameters governing these interactions will be identified through mathematical sensitivity analyses. These results will incorporate, and be tested against, known clinical and experimental data.