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Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1
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Proc Natl Acad Sci U S A. 2014 Aug 5. pii: 201406663. [Epub ahead of print]
Alison L. Hilla,b,1,2, Daniel I. S. Rosenblooma,c,1, Feng Fud, Martin A. Nowaka, and Robert F. Silicianoe,f
aProgram for Evolutionary Dynamics, Department of Mathematics, and Department of Organismic and Evolutionary Biology, and bBiophysics Program
and Harvard-MIT Division of Health Sciences and Technology, Harvard University, Cambridge, MA 02138; cDepartment of Biomedical Informatics, Columbia
University Medical Center, New York, NY 10032; dInstitute of Integrative Biology, Eidgenossische Technische Hochschule Zurich, 8092 Zurich, Switzerland;
and eDepartment of Medicine and fHoward Hughes Medical Institute, The Johns Hopkins University School of Medicine, Baltimore, MD 21205
Edited by John M. Coffin, Tufts University School of Medicine, Boston, MA, and approved July 9, 2014 (received for review April 12, 2014)
Significance
HIV infection cannot be cured by current antiretroviral drugs, due to the presence of long-lived latently infected cells. New antilatency drugs are being tested in clinical trials, but major unknowns remain. It is unclear how much latent virus must be eliminated for a cure, which remains difficult to answer empirically due to few case studies and limited sensitivity of viral reservoir assays. In this paper, we introduce a mathematical model of HIV dynamics to calculate the likelihood and timing of viral rebound following antilatency treatment. We derive predictions for the required efficacy of antilatency drugs, and demonstrate that rebound times may be highly variable and occur after years of remission. These results will aid in designing and interpreting HIV cure studies.
Abstract
Massive research efforts are now underway to develop a cure for HIV infection, allowing patients to discontinue lifelong combination antiretroviral therapy (ART). New latency-reversing agents (LRAs) may be able to purge the persistent reservoir of latent virus in resting memory CD4+ T cells, but the degree of reservoir reduction needed for cure remains unknown. Here we use a stochastic model of infection dynamics to estimate the efficacy of LRA needed to prevent viral rebound after ART interruption. We incorporate clinical data to estimate population-level parameter distributions and outcomes. Our findings suggest that ~2,000-fold reductions are required to permit a majority of patients to interrupt ART for 1 y without rebound and that rebound may occur suddenly after multiple years. Greater than 10,000-fold reductions may be required to prevent rebound altogether. Our results predict large variation in rebound times following LRA therapy, which will complicate clinical management. This model provides benchmarks for moving LRAs from the laboratory to the clinic and can aid in the design and interpretation of clinical trials. These results also apply to other interventions to reduce the latent reservoir and can explain the observed return of viremia after months of apparent cure in recent bone marrow transplant recipients and an immediately-treated neonate.
We believe that these modeling efforts will provide a quantitative framework for interpreting clinical trials of any reservoir-reduction strategy.
Our model is, to our knowledge, the first to quantify the required efficacy of LRAs for HIV-1 and set goals for therapy. For a wide range of parameters, we find that therapies must reduce the LR by at least 2 orders of magnitude to meaningfully increase time to rebound after ART interruption (upward inflection in Figs. 2B and 3 A, II; B, II; C, II), and that reductions of approximately 4 orders of magnitude are needed for half of patients to clear the infection (Figs. 3 A, I; B, I; C, I; and 4). Standard deviations in rebound times of many months are expected, owing to substantial variation in reactivation times after effective LRA therapy brings the infection to an activation-limited regime. Though the efficacy required for these beneficial outcomes likely exceeds the reach of current drugs, our results permit some optimism: We show for the first time, to our knowledge, that reactivation of all cells in the reservoir is not necessary for cessation of ART. This is because some cells in the LR will die before reactivating or, following activation, will fail to produce a chain of infections leading to rebound. On a more cautionary note, the wide distribution in reactivation times necessitates careful monitoring of patients, as rebound may occur even after long periods of viral suppression.
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