Models of SIV rebound after treatment interruption that involve multiple reactivation events

Abstract

In order to assess the efficacy of novel HIV-1 treatments leading to a functional cure, the time to viral rebound is frequently used as a surrogate endpoint. The longer the time to viral rebound, the more efficacious the therapy. In support of such an approach, mathematical models serve as a connection between the size of the latent reservoir and the time to HIV-1 rebound after treatment interruption. The simplest of such models assumes that a single successful latent cell reactivation event leads to observable viremia after a period of exponential viral growth. Here we consider a generalization developed by Pinkevych et al. and Hill et al. of this simple model in which multiple reactivation events can occur, each contributing to the exponential growth of the viral load. We formalize and improve the previous derivation of the dynamics predicted by this model, and use the model to estimate relevant biological parameters from SIV rebound data. We confirm a previously described effect of very early antiretroviral therapy (ART) initiation on the rate of recrudescence and the viral load growth rate after treatment interruption. We find that every day ART initiation is delayed results in a 39% increase in the recrudescence rate (95% credible interval: [18%, 62%]), and a 11% decrease of the viral growth rate (95% credible interval: [4%, 20%]). We show that when viral rebound occurs early relative to the viral load doubling time, a model with multiple successful reactivation events fits the data better than a model with only a single successful reactivation event.

Assessing the impact of autologous neutralizing antibodies on viral rebound in postnatally SHIV-infected ART-treated infant rhesus macaques

“…Our results suggest that antibodies play a dual role, altering both the outcome of a latent cell activation, and the speed with which plasma viremia crosses the detection threshold. Interestingly, a larger latent reservoir is associated with a shorter delay between activation and detectable viremia, suggesting that after the successful activation occurs, there are subsequent activations that contribute to overall viremia during this stochastic phase, consistent with model predictions for SIV in van Dorp et al (2020) [44].…”

“…Our model predicts that larger latent reservoir sizes are associated with shorter delay times between successful activation and detectable viremia, which suggests that the latent reservoir has some impact on the net growth rate of viral loads during rebound. We conjecture that this effect may be associated with secondary activations contributing to viral load as in Van Dorp et al (2020) [44]. This is also supported by experimental observations: for example, experiments where treatment interruptions were conducted on macaques that had been infected with a genetically barcoded SIV strain indicated that a significant number of cells could reactivate successfully from the latent reservoir [35].…”

Unified model of short- and long-term HIV viral rebound for clinical trial planning

“…Presumably, the reservoir would similarly continue to decay post-ATI but pre-rebound, since the viral load remaining undetectable implies that robust viral replication, which may replenish the reservoir, is unlikely. Further, we recently showed that short-term viral rebounds are actually better explained by multiple successful latent cell activations in succession, with detectable viraemia composed of virus arising from replication in multiple lineages [56]. Lastly and importantly, we completely neglected the inherent heterogeneity of the latent reservoir.…”

Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion

“…Several models have been proposed to explain the mechanisms behind viral rebound following ATI. The studies by Hill et al [35,36], Pinkevych et al [37,38], Fennessey et al [39], and van Dorp et al [40] hypothesized rebound as a stochastic process due to the reactivation of latently infected cells that release virus and initiate a chain of other successful infection events. Yet, in PTC, viral load is kept at a low level despite a large reservoir size in some people.…”