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Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion.
Phan, Tin; Conway, Jessica M; Pagane, Nicole; Kreig, Jasmine; Sambaturu, Narmada; Iyaniwura, Sarafa; Li, Jonathan Z; Ribeiro, Ruy M; Ke, Ruian; Perelson, Alan S.
Affiliation
  • Phan T; Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Conway JM; Department of Mathematics, Pennsylvania State University, College Township, PA, USA.
  • Pagane N; Department of Biology, Pennsylvania State University, College Township, PA, USA.
  • Kreig J; Program in Computational and Systems Biology, Massachusetts Institute of Technology; Cambridge, MA, USA.
  • Sambaturu N; Ragon Institute of MGH, MIT, and Harvard; Cambridge, MA, USA.
  • Iyaniwura S; Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Li JZ; Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Ribeiro RM; Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA.
  • Ke R; Department of Medicine, Division of Infectious Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Perelson AS; Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA.
bioRxiv ; 2024 May 05.
Article in En | MEDLINE | ID: mdl-38746144
ABSTRACT
Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: BioRxiv Year: 2024 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: BioRxiv Year: 2024 Document type: Article Affiliation country: Estados Unidos