Stochastic effects are important in intrahost HIV evolution even when viral loads are high
Name
Chakraborty-2012- Stochastic effects are important.pdf
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2.6 MB
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Author(s)
Read, Elizabeth L.
Tovo-Dwyer, Allison A.
Chakraborty, Arup K
Date Issued
October 2012
Journal
Proceedings of the National Academy of Sciences of the United States of America
Publisher
National Academy of Sciences (U.S.)
Citation
Read, E. L., A. A. Tovo-Dwyer, and A. K. Chakraborty. “Stochastic Effects Are Important in Intrahost HIV Evolution Even When Viral Loads Are High.” Proceedings of the National Academy of Sciences 109.48 (2012): 19727–19732.
Version
Final published version
Abstract
Blood plasma viral loads and the time to progress to AIDS differ widely among untreated HIV-infected humans. Although people with certain HLA (HLA-I) alleles are more likely to control HIV infections without therapy, the majority of such untreated individuals exhibit high viral loads and progress to AIDS. Stochastic effects are considered unimportant for evolutionary dynamics in HIV-infected people when viral load is high or when selective forces strongly drive mutation. We describe a computational study of host–pathogen interaction demonstrating that stochastic effects can have a profound influence on disease dynamics, even in cases of high viral load and strong selective pressure. These stochastic effects are pronounced when the virus must traverse a fitness “barrier” in sequence space to escape the host’s cytotoxic T-lymphocyte (CTL) response, as often occurs when a fitness defect imposed by a CTL-driven mutation must be compensated for by other mutations. These “barrier-crossing” events are infrequent and stochastic, resulting in divergent disease outcomes in genetically identical individuals infected by the same viral strain. Our results reveal how genetic determinants of the CTL response control the probability with which an individual is able to control HIV infection indefinitely, and thus provide clues for vaccine design.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Chemistry
Massachusetts Institute of Technology. Department of Physics
Ragon Institute of MGH, MIT and Harvard
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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.
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DOI of Published Version
https://doi.org/10.1073/pnas.1206940109
