Objectives: To est. the relative efficiency of transmission of different HIV-1 drug-resistance mutations from patients failing treatment, considered as potential transmitters (PTs), to seroconverters (SCs). Design: Ecol. cross-sectional study. Methods: HIV-1 protease and reverse transcriptase (RT) sequence data, obtained from 155 SCs and 2,690 PTs at the Department of Mol. Biol. of the University of Siena, Italy, in the period 1997-2004 were used. The efficiency of transmission was studied by odds ratio (OR) anal. and evaluation of 95% confidence intervals (95% CIs). For mutations not detected in viruses from SCs, a binomial probability model was used, assuming P-values <0.05 as indicative of a neg. selection at transmission. Results: The overall prevalence of drug mutations assocd. with nucleoside reverse transcriptase inhibitors (NRTIs), non-NRTIs (NNRTIs) and protease inhibitors (PIs) was 13.2%, 4.6% and 2.0% in SCs, and 69.9%, 27.6% and 33.7% in PTs, resp. Among RT mutations present both in PTs and SCs, M184I/V and T215F/Y had the lowest relative efficiency of transmission, whereas V118I, Y181C/I and K219E/Q showed the highest relative efficiency. Of the three major protease mutations that could be evaluated by this approach, M46I/L had a lower rate of transmission than I84V and L90M. Among the mutations not detected in viruses from SCs, the RT E44D, V108I, Q151M and Y188C/H/L, and the protease D30N, G48V and V82A/F/S/T substitutions appeared to be neg. selected. Conclusions: The transmission rate of drug-resistant HIV-1 variants may be differentially affected by the mutational pattern. The binomial model enabled to evaluate the neg. selection against specific substitutions. Given the low prevalence of some resistance mutations in SCs, very large data sets are required to evaluate the potential selection of such mutations. [on SciFinder (R)]
Evidence of differential selection of HIV-1 variants carrying drug-resistant mutations in seroconverters / S. Corvasce, M. Violin, L. Romano, F. Razzolini, I. Vicenti, A. Galli, P. Duca, I. Caramma, C. Balotta, M. Zazzi. - In: ANTIVIRAL THERAPY. - ISSN 1359-6535. - 11:3(2006), pp. 329-334.
Evidence of differential selection of HIV-1 variants carrying drug-resistant mutations in seroconverters
S. Corvasce;M. Violin;A. Galli;P. Duca;I. Caramma;C. Balotta;
2006
Abstract
Objectives: To est. the relative efficiency of transmission of different HIV-1 drug-resistance mutations from patients failing treatment, considered as potential transmitters (PTs), to seroconverters (SCs). Design: Ecol. cross-sectional study. Methods: HIV-1 protease and reverse transcriptase (RT) sequence data, obtained from 155 SCs and 2,690 PTs at the Department of Mol. Biol. of the University of Siena, Italy, in the period 1997-2004 were used. The efficiency of transmission was studied by odds ratio (OR) anal. and evaluation of 95% confidence intervals (95% CIs). For mutations not detected in viruses from SCs, a binomial probability model was used, assuming P-values <0.05 as indicative of a neg. selection at transmission. Results: The overall prevalence of drug mutations assocd. with nucleoside reverse transcriptase inhibitors (NRTIs), non-NRTIs (NNRTIs) and protease inhibitors (PIs) was 13.2%, 4.6% and 2.0% in SCs, and 69.9%, 27.6% and 33.7% in PTs, resp. Among RT mutations present both in PTs and SCs, M184I/V and T215F/Y had the lowest relative efficiency of transmission, whereas V118I, Y181C/I and K219E/Q showed the highest relative efficiency. Of the three major protease mutations that could be evaluated by this approach, M46I/L had a lower rate of transmission than I84V and L90M. Among the mutations not detected in viruses from SCs, the RT E44D, V108I, Q151M and Y188C/H/L, and the protease D30N, G48V and V82A/F/S/T substitutions appeared to be neg. selected. Conclusions: The transmission rate of drug-resistant HIV-1 variants may be differentially affected by the mutational pattern. The binomial model enabled to evaluate the neg. selection against specific substitutions. Given the low prevalence of some resistance mutations in SCs, very large data sets are required to evaluate the potential selection of such mutations. [on SciFinder (R)]Pubblicazioni consigliate
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