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Assessing predicted HIV-1 replicative capacity in a clinical setting

Kouyos, R. D. and von Wyl, V. and Hinkley, T. and Petropoulos, C. J. and Haddad, M. and Whitcomb, J. M. and Boni, J. and Yerly, S. and Cellerai, C. and Klimkait, T. and Gunthard, H. F. and Bonhoeffer, S. and Swiss HIV Cohort Study, . (2011) Assessing predicted HIV-1 replicative capacity in a clinical setting. PLoS Pathogens, Vol. 7, H. 11 , e1002321.

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Official URL: http://edoc.unibas.ch/dok/A6004822

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Abstract

HIV-1 replicative capacity (RC) provides a measure of within-host fitness and is determined in the context of phenotypic drug resistance testing. However it is unclear how these in-vitro measurements relate to in-vivo processes. Here we assess RCs in a clinical setting by combining a previously published machine-learning tool, which predicts RC values from partial pol sequences with genotypic and clinical data from the Swiss HIV Cohort Study. The machine-learning tool is based on a training set consisting of 65000 RC measurements paired with their corresponding partial pol sequences. We find that predicted RC values (pRCs) correlate significantly with the virus load measured in 2073 infected but drug naïve individuals. Furthermore, we find that, for 53 pairs of sequences, each pair sampled in the same infected individual, the pRC was significantly higher for the sequence sampled later in the infection and that the increase in pRC was also significantly correlated with the increase in plasma viral load and with the length of the time-interval between the sampling points. These findings indicate that selection within a patient favors the evolution of higher replicative capacities and that these in-vitro fitness measures are indicative of in-vivo HIV virus load.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedizin > Division of Medical Microbiology > Molecular Virology (Klimkait)
UniBasel Contributors:Klimkait, Thomas
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:Public Library of Science
ISSN:1553-7366
e-ISSN:1553-7374
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:13 Oct 2017 07:47
Deposited On:06 Dec 2013 09:36

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