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Francoise Brun-Vézinet

Publications and source records attributed to Francoise Brun-Vézinet.

4 recordsLinked to original sources
PubMed2005

Molecular testing of multiple HIV-1 transmissions in a criminal case.

OBJECTIVE: To test the a priori hypothesis of HIV-1 transmission from one suspect to six recipients in a criminal case. METHODS: Partial pol and/or env sequences were obtained for at least two samples of the suspect and the victims. Appropriate local controls were sampled based on epidemiological and subtype criteria. Phylogenetic testing was performed using different reconstruction methods. RESULTS: Phylogenetic analyses consistently inferred a monophyletic cluster for the suspect and victim samples in both genome regions. This was highly supported by parametric and non-parametric bootstrapping techniques. Moreover, the controls most closely related to the suspect-victim cluster had a similar geographical origin to the suspect. CONCLUSIONS: Taking into account the limitations on the conclusions that can be drawn from molecular investigations we could infer that our molecular data is consistent with a scenario of multiple HIV transmission between suspect and victims.

Bayes Theorem↗
PubMed2004

High frequency of selection of K65R and Q151M mutations in HIV-2 infected patients receiving nucleoside reverse transcriptase inhibitors containing regimen.

The objective of the study was to determine retrospectively which substitutions in the reverse transcriptase (RT) gene are selected in vivo during nucleoside RT inhibitors (NRTI) containing regimen in HIV-2 infected subjects. Thirty-four HIV-2 patients having received NRTI-containing regimen with available specimens and amplifiable RT gene were studied. Analyses of RT gene were undertaken after a median NRTI exposure of 51 months (range: 5-128). Mutations at positions known to be involved in HIV-1 resistance were observed in 26/34 patients. Selection of Q151M mutation was observed in nine out of 34 isolates (26%) after a median NRTIs exposure of 41 months (range: 12-77). In 8/9 cases, Q151M mutation was associated with other substitutions at positions known to be involved in HIV-1 resistance: K65R (n = 6), D67N (n = 1), N69S or T (n = 2), K70R (n = 3), M184V (n = 4), S215Y (n = 1). Compared with HIV-1 infection, there is a high frequency of selection of Q151M mutation in HIV-2 infected patients receiving various combinations of NRTIs. In these highly thymidine analogue pretreated patients, the selection of thymidine analogue mutations was low suggesting that the pathway to resistance is very different between these two viruses.

Anti-HIV Agents↗
PubMed2003

HIV-1 protease and reverse transcriptase mutation patterns responsible for discordances between genotypic drug resistance interpretation algorithms.

Several rules-based algorithms have been developed to interpret results of HIV-1 genotypic resistance tests. To assess the concordance of these algorithms and to identify sequences causing interalgorithm discordances, we applied four publicly available algorithms to the sequences of isolates from 2,045 individuals in northern California. Drug resistance interpretations were classified as S for susceptible, I for intermediate, and R for resistant. Of 30,675 interpretations (2,045 sequences x 15 drugs), 4.4% were completely discordant, with at least one algorithm assigning an S and another an R; 29.2% were partially discordant, with at least one algorithm assigning an S and another an I, or at least one algorithm assigning an I and another an R; and 66.4% displayed complete concordance, with all four algorithms assigning the same interpretation. Discordances between nucleoside reverse transcriptase inhibitor interpretations usually resulted from several simple, frequently occurring mutational patterns. Discordances between protease inhibitor interpretations resulted from a larger number of more complex mutation patterns. Discordances between nonnucleoside reverse transcriptase inhibitor interpretations were uncommon and resulted from a small number of individual drug resistance mutations. Determining the clinical significance of these mutation patterns responsible for interalgorithm discordances will improve interalgorithm concordance and the accuracy of genotypic resistance interpretation.

Algorithms↗