Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1
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[superscript +] T...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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National Academy of Sciences (U.S.)
2015
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| Online Access: | http://hdl.handle.net/1721.1/95747 |
| _version_ | 1811096531346915328 |
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| author | Hill, Alison Lynn Rosenbloom, Daniel I. S. Fu, Feng Nowak, Martin A. Siliciano, Robert F. |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology Hill, Alison Lynn Rosenbloom, Daniel I. S. Fu, Feng Nowak, Martin A. Siliciano, Robert F. |
| author_sort | Hill, Alison Lynn |
| collection | MIT |
| description | 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[superscript +] 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. |
| first_indexed | 2024-09-23T16:45:09Z |
| format | Article |
| id | mit-1721.1/95747 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:45:09Z |
| publishDate | 2015 |
| publisher | National Academy of Sciences (U.S.) |
| record_format | dspace |
| spelling | mit-1721.1/957472022-10-03T08:02:31Z Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1 Hill, Alison Lynn Rosenbloom, Daniel I. S. Fu, Feng Nowak, Martin A. Siliciano, Robert F. Harvard University--MIT Division of Health Sciences and Technology Hill, Alison Lynn 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[superscript +] 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. American Foundation for AIDS Research. Research Consortium on HIV Eradication (Grant 108165-50-RGRL) Howard Hughes Medical Institute Johns Hopkins Center for AIDS Research Bill & Melinda Gates Foundation (Grand Challenges Explorations Grant OPP1044503) National Institutes of Health (U.S.) (Martin Delaney Collaboratory of AIDS Researchers for Eradication. Grant AI096113) National Institutes of Health (U.S.) (Delaney AIDS Research Enterprise Collaboratory. Grant 1U19AI096109) 2015-03-03T16:49:00Z 2015-03-03T16:49:00Z 2014-08 2014-04 Article http://purl.org/eprint/type/JournalArticle 0027-8424 1091-6490 http://hdl.handle.net/1721.1/95747 Hill, Alison L., Daniel I. S. Rosenbloom, Feng Fu, Martin A. Nowak, and Robert F. Siliciano. “Predicting the Outcomes of Treatment to Eradicate the Latent Reservoir for HIV-1.” Proceedings of the National Academy of Sciences 111, no. 37 (August 5, 2014): 13475–13480. © 2014 National Academy of Sciences en_US http://dx.doi.org/10.1073/pnas.1406663111 Proceedings of the National Academy of Sciences of the United States of America Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf National Academy of Sciences (U.S.) National Academy of Sciences (U.S.) |
| spellingShingle | Hill, Alison Lynn Rosenbloom, Daniel I. S. Fu, Feng Nowak, Martin A. Siliciano, Robert F. Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1 |
| title | Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1 |
| title_full | Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1 |
| title_fullStr | Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1 |
| title_full_unstemmed | Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1 |
| title_short | Predicting the outcomes of treatment to eradicate the latent reservoir for HIV-1 |
| title_sort | predicting the outcomes of treatment to eradicate the latent reservoir for hiv 1 |
| url | http://hdl.handle.net/1721.1/95747 |
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