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

Bahareh Khazaei, Javad Salimi Sartakhti, Mohammad Hossein Manshaei, Quanyan Zhu, Mehdi Sadeghi, Seyed Rasoul Mousavi

Research output: Contribution to journalArticle

Abstract

Background and Objective Understanding the dynamics of human immunodeficiency virus (HIV) is essential for depicting, developing, and investigating effective treatment strategies. HIV infects several types of immune cells, but its main target is to destroy helper T-cells. In the lymph nodes, the infected T-cells interact with each other and their environment to obtain more resources. According to infectivity and replicative capacity of T-cells in the HIV infection process, they can be divided into four phenotypes. Although genetic mutations in the reverse transcription that beget these phenotypes are random, the framework by which a phenotype become favored is affected by the environment and neighboring phenotypes. Moreover, the HIV disease has all components of an evolutionary process, including replication, mutation, and selection. Methods We propose a novel structure-based game-theoretic model for the evolution of HIV-1-Infected CD4+T-cells and invasion of the immune system. We discuss the theoretical basis of the stable equilibrium states of the evolutionary dynamics of four T-cells types as well as its significant results to understand and control HIV infection. The results include the importance of genetic variations and the process of establishing evolutionary dynamics of the virus quasispecies. Results Our results show that there is a direct dependency between some parameters such as mutation rates and the stability of equilibrium states in the HIV infection. This is an interesting result because these parameters can be changed by some pharmacotherapies and alternative treatments. Our model indicates that in an appropriate treatment the relative frequency of the wild type of virus quasispecies can be decreased in the population. Consequently, this can cause delaying the emergence of the AIDS phase. To assess the model, we investigate two new treatments for HIV. The results show that our model can predict the treatment results. Conclusions The paper shows that a structured-based evolutionary game theory can model the evolutionary dynamics of the infected T-cells and virus quasispecies. The model predicts certain aspects of the HIV infection process under several treatments.

Original languageEnglish (US)
Pages (from-to)1-14
Number of pages14
JournalComputer Methods and Programs in Biomedicine
Volume152
DOIs
StatePublished - Dec 1 2017

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T-cells
Viruses
HIV-1
HIV
T-Lymphocytes
Virus Diseases
Phenotype
Reticuloendotheliosis virus
Therapeutics
Genetic Phenomena
Game Theory
Mutation
Mutation Rate
Helper-Inducer T-Lymphocytes
Reverse Transcription
Drug therapy
Immune System
Acquired Immunodeficiency Syndrome
Theoretical Models
Immune system

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics

Cite this

HIV-1-infected T-cells dynamics and prognosis : An evolutionary game model. / Khazaei, Bahareh; Sartakhti, Javad Salimi; Manshaei, Mohammad Hossein; Zhu, Quanyan; Sadeghi, Mehdi; Mousavi, Seyed Rasoul.

In: Computer Methods and Programs in Biomedicine, Vol. 152, 01.12.2017, p. 1-14.

Research output: Contribution to journalArticle

Khazaei, Bahareh ; Sartakhti, Javad Salimi ; Manshaei, Mohammad Hossein ; Zhu, Quanyan ; Sadeghi, Mehdi ; Mousavi, Seyed Rasoul. / HIV-1-infected T-cells dynamics and prognosis : An evolutionary game model. In: Computer Methods and Programs in Biomedicine. 2017 ; Vol. 152. pp. 1-14.
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