Title
Estimating the individualized HIV-1 genetic barrier to resistance using a nelfinavir fitness landscape.
Abstract
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.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).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.
Year
DOI
Venue
2010
10.1186/1471-2105-11-409
BMC Bioinformatics
Keywords
Field
DocType
algorithms,genetics,microarrays,bioinformatics,fitness landscape,mutation,reverse engineering
Nelfinavir,Fitness landscape,Biology,Drug resistance,Network Functions Virtualization,Data sequences,Bioinformatics,Genetics,Mutation
Journal
Volume
Issue
ISSN
11
1
1471-2105
Citations 
PageRank 
References 
11
0.40
4
Authors
11
Name
Order
Citations
PageRank
Kristof Theys1171.77
Koen Deforche2727.19
Gertjan Beheydt3110.40
Yves Moreau41202105.05
K Van Laethem5475.33
Philippe Lemey69614.23
Ricardo J Camacho7110.40
Soo-Yon Rhee8717.16
Robert W Shafer98221.01
Eric Van Wijngaerden10212.00
Anne-Mieke Vandamme11799.29