Estimating HIV Evolutionary Pathways and the Genetic Barrier to Drug Resistance
1Max Planck Institute for Informatics, Saarbrücken, 2Institute of Virology, University of Cologne, Cologne, 3Max Planck Institute of Molecular Plant Physiology, Golm, and 4Center of Advanced European Studies and Research, Bonn, Germany
Background.
The evolution of drug‐resistant viruses challenges the management of human immunodeficiency virus (HIV) infections. Understanding this evolutionary process is important for the design of effective therapeutic strategies.
Methods.
We used mutagenetic trees, a family of probabilistic graphical models, to describe the accumulation of resistance‐associated mutations in the viral genome. On the basis of these models, we defined the genetic barrier, a quantity that summarizes the difficulty for the virus to escape from the selective pressure of the drug by developing escape mutations.
Results.
From HIV reverse‐transcriptase sequences that had been obtained from treated patients, we derived evolutionary models for zidovudine, zidovudine plus lamivudine, and zidovudine plus didanosine. The genetic barriers to resistance to zidovudine, stavudine, lamivudine, and didanosine, for the above 3 regimens, were computed and analyzed. We found both the mode and the rate of development of resistance to be heterogeneous. The genetic barrier to zidovudine resistance was increased if lamivudine was added to zidovudine but was decreased for didanosine. The barrier to lamivudine resistance was maintained with zidovudine plus didanosine, whereas the barrier to didanosine resistance was reduced most with zidovudine plus lamivudine.
Conclusion.
Mutagenetic trees provide a quantitative picture of the evolution of drug resistance. The genetic barrier is a useful tool for design of effective treatment strategies.
Received 23 September 2004; accepted 3 January 2005; electronically published 28 April 2005.
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Presented in part: XII International HIV Drug Resistance Workshop, Los Cabos, Mexico, 10–14 June 2003 (abstract 97); XIII International HIV Drug Resistance Workshop, Teneriffe, Spain, 8–12 June 2004 (abstract 111).
Financial support: Deutsche Forschungsgemeinschaft (grants HO 1582/1‐3, KA 1569/1‐3, and BE 3217/1‐1); German Federal Ministry of Education and Research (grant 031U117). The research at Max‐Planck Institute for Informatics was performed in the context of the EU Network of Excellence Biosapiens (EU grant LSHG‐CT‐2003‐503265).
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Present affiliation: Department of Mathematics, University of California at Berkeley, Berkeley.





