• Call for Physical Sciences Papers
  • Sign-up for PNAS eTOC Alerts

Post-treatment control of HIV infection

  1. Alan S. Perelsonb,1
  1. aDepartment of Mathematics, Pennsylvania State University, University Park, PA 16802; and
  2. bTheoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM 87545

  1. Edited by Charles S. Peskin, New York University, Manhattan, NY, and approved March 13, 2015 (received for review October 8, 2014)

Significance

Recent reports suggest that antiretroviral therapy (ART) initiated early after HIV infection increases the likelihood of post-treatment control (PTC) in which plasma virus remains undetectable after treatment cessation. However, only a small fraction of patients treated early attain PTC. We develop a mathematical model of HIV infection that provides insight into these phenomena, suggesting that treatments restricting or reducing the latent reservoir size may allow immune responses to control infection posttreatment. Our model makes predictions about immune response strengths and latent reservoir sizes needed for a patient taken off treatment to exhibit PTC that may help guide future studies.

Abstract

Antiretroviral therapy (ART) for HIV is not a cure. However, recent studies suggest that ART, initiated early during primary infection, may induce post-treatment control (PTC) of HIV infection with HIV RNA maintained at <50 copies per mL. We investigate the hypothesis that ART initiated early during primary infection permits PTC by limiting the size of the latent reservoir, which, if small enough at treatment termination, may allow the adaptive immune response to prevent viral rebound (VR) and control infection. We use a mathematical model of within host HIV dynamics to capture interactions among target cells, productively infected cells, latently infected cells, virus, and cytotoxic T lymphocytes (CTLs). Analysis of our model reveals a range in CTL response strengths where a patient may show either VR or PTC, depending on the size of the latent reservoir at treatment termination. Below this range, patients will always rebound, whereas above this range, patients are predicted to behave like elite controllers. Using data on latent reservoir sizes in patients treated during primary infection, we also predict population-level VR times for noncontrollers consistent with observations.

Footnotes

  • ↵1To whom correspondence should be addressed. Email: asp{at}lanl.gov.

Online Impact