HIV-1-infected T-cells dynamics and prognosis: An evolutionary game model

Area of Science:

• Evolutionary biology
• Immunology
• Mathematical modeling

Background:

• Human immunodeficiency virus (HIV) primarily targets and destroys helper T-cells, crucial components of the immune system.
• HIV-infected T-cells exhibit diverse phenotypes based on infectivity and replication, influenced by environmental factors and genetic mutations.
• HIV infection exhibits evolutionary characteristics, including replication, mutation, and selection.

Purpose of the Study:

• To develop a novel structure-based game-theoretic model for understanding the evolution of HIV-1-infected CD4+ T-cells.
• To analyze the stable equilibrium states of T-cell evolutionary dynamics and their implications for HIV control.
• To explore the role of genetic variations in the evolutionary dynamics of HIV quasispecies.

Main Methods:

• A structure-based game-theoretic model was developed to simulate HIV-1-infected CD4+ T-cell evolution.
• Theoretical analysis of stable equilibrium states in the evolutionary dynamics of four T-cell types.
• Investigation of genetic variations and their impact on HIV quasispecies evolution.

Main Results:

• Mutation rates directly influence the stability of equilibrium states in HIV infection dynamics.
• The model predicts that specific treatments can decrease the frequency of wild-type HIV, potentially delaying AIDS progression.
• The model accurately predicted outcomes for two novel HIV treatment strategies.

Conclusions:

• Evolutionary game theory provides a robust framework for modeling the dynamics of HIV-infected T-cells and viral quasispecies.
• The developed model offers insights into predicting HIV infection progression under various treatment interventions.