Bayesian network analyses of resistance pathways against efavirenz and nevirapine
| Autor: | Koen, Deforche, Ricardo J, Camacho, Zehave, Grossman, Marcelo A, Soares, Kristel, Van Laethem, David A, Katzenstein, P Richard, Harrigan, Rami, Kantor, Robert, Shafer, Anne-Mieke, Vandamme, Louise Bruun, Jørgensen |
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| Rok vydání: | 2008 |
| Předmět: |
Cyclopropanes
Efavirenz Nevirapine Databases Factual Anti-HIV Agents Immunology Drug resistance Biology Emtricitabine Article chemistry.chemical_compound immune system diseases Drug Resistance Viral medicine Immunology and Allergy Humans Genetics Reverse-transcriptase inhibitor Nucleoside analogue virus diseases Lamivudine Bayes Theorem biochemical phenomena metabolism and nutrition Virology Reverse transcriptase HIV Reverse Transcriptase Benzoxazines Infectious Diseases chemistry Alkynes Mutation HIV-1 Reverse Transcriptase Inhibitors medicine.drug Signal Transduction |
| Zdroj: | AIDS (London, England). 22(16) |
| ISSN: | 1473-5571 |
| Popis: | Objective To clarify the role of novel mutations selected by treatment with efavirenz or nevirapine, and investigate the influence of HIV-1 subtype on nonnucleoside reverse transcriptase inhibitor (nNRTI) resistance pathways. Design By finding direct dependencies between treatment-selected mutations, the involvement of these mutations as minor or major resistance mutations against efavirenz, nevirapine, or coadministrated nucleoside analogue reverse transcriptase inhibitors (NRTIs) is hypothesized. In addition, direct dependencies were investigated between treatment-selected mutations and polymorphisms, some of which are linked with subtype, and between NRTI and nNRTI resistance pathways. Methods Sequences from a large collaborative database of various subtypes were jointly analyzed to detect mutations selected by treatment. Using Bayesian network learning, direct dependencies were investigated between treatment-selected mutations, NRTI and nNRTI treatment history, and known NRTI resistance mutations. Results Several novel minor resistance mutations were found: 28K and 196R (for resistance against efavirenz), 101H and 138Q (nevirapine), and 31L (lamivudine). Robust interactions between NRTI mutations (65R, 74V, 75I/M, and 184V) and nNRTI resistance mutations (100I, 181C, 190E and 230L) may affect resistance development to particular treatment combinations. For example, an interaction between 65R and 181C predicts that the nevirapine and tenofovir and lamivudine/emtricitabine combination should be more prone to failure than efavirenz and tenofovir and lamivudine/emtricitabine. Conclusion Bayesian networks were helpful in untangling the selection of mutations by NRTI versus nNRTI treatment, and in discovering interactions between resistance mutations within and between these two classes of inhibitors. |
| Databáze: | OpenAIRE |
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