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. 2010 Aug 3:11:409.
doi: 10.1186/1471-2105-11-409.

Estimating the individualized HIV-1 genetic barrier to resistance using a nelfinavir fitness landscape

Kristof Theys  1 , Koen Deforche, Gertjan Beheydt, Yves Moreau, Kristel van Laethem, Philippe Lemey, Ricardo J Camacho, Soo-Yon Rhee, Robert W Shafer, Eric Van Wijngaerden, Anne-Mieke Vandamme
Affiliations

Estimating the individualized HIV-1 genetic barrier to resistance using a nelfinavir fitness landscape

Kristof Theys et al. BMC Bioinformatics. .

Abstract

Background: Failure on Highly Active Anti-Retroviral Treatment is often accompanied with development of antiviral resistance to one or more drugs included in the treatment. In general, the virus is more likely to develop resistance to drugs with a lower genetic barrier. Previously, we developed a method to reverse engineer, from clinical sequence data, a fitness landscape experienced by HIV-1 under nelfinavir (NFV) treatment. By simulation of evolution over this landscape, the individualized genetic barrier to NFV resistance may be estimated for an isolate.

Results: We investigated the association of estimated genetic barrier with risk of development of NFV resistance at virological failure, in 201 patients that were predicted fully susceptible to NFV at baseline, and found that a higher estimated genetic barrier was indeed associated with lower odds for development of resistance at failure (OR 0.62 (0.45 - 0.94), per additional mutation needed, p = .02).

Conclusions: Thus, variation in individualized genetic barrier to NFV resistance may impact effective treatment options available after treatment failure. If similar results apply for other drugs, then estimated genetic barrier may be a new clinical tool for choice of treatment regimen, which allows consideration of available treatment options after virological failure.

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Figures

Figure 1
Figure 1
Genotypic correlates of genetic barrier. Impact of protease mutations and polymorphisms on the estimated genetic barrier to nelfinavir (NFV) resistance. For each mutation, the prevalence is indicated in the data set of protease inhibitor naive patients, which are all predicted as fully susceptible to NFV.
See this image and copyright information in PMC

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