BACKGROUND: The detection of mutations associated with drug resistance in HIV type-1 might be increased by applying minority species assays capable of identifying low frequency mutations in comparison with the use of population sequencing alone. Because minority species assays are mutation-specific, the benefit of this approach differs depending on the mutation being detected. METHODS: We performed a systematic review of published data reporting detection of genotypic drug resistance using allele-specific (AS)-PCR minority assays and by standard DNA sequencing in drug-naive populations. We calculated the fold increase of mutation detection for each study and pooled these via meta-analysis, displaying results using Forest plots. RESULTS: Our studies revealed an increase in detection of 1.9-fold (95% confidence interval [CI] 1.3-2.7; P < 0.0005) for K103N, 4.4-fold (95% CI 1.2-16.6; P = 0.026) for Y181C, 4.8-fold (95% CI 1.5-15.1; P = 0.008) for L90M and 8.7-fold (95% CI 4.0-18.6; P < 0.0005) for M184V. We found no relationship between AS-PCR assay sensitivity and frequency of additional mutation detection. CONCLUSIONS: Additional detection of drug resistance mutations using AS-PCR minority mutation assays vary significantly depending on the mutation examined; however, the most marked increase in detection of resistance mutations was observed for M184V, a mutation seldom detected by standard techniques in drug-naive patients. We suggest that the presence of drug resistance mutations can be more accurately estimated using a combination of AS-PCR and standard genotyping.
BACKGROUND: The detection of mutations associated with drug resistance in HIV type-1 might be increased by applying minority species assays capable of identifying low frequency mutations in comparison with the use of population sequencing alone. Because minority species assays are mutation-specific, the benefit of this approach differs depending on the mutation being detected. METHODS: We performed a systematic review of published data reporting detection of genotypic drug resistance using allele-specific (AS)-PCR minority assays and by standard DNA sequencing in drug-naive populations. We calculated the fold increase of mutation detection for each study and pooled these via meta-analysis, displaying results using Forest plots. RESULTS: Our studies revealed an increase in detection of 1.9-fold (95% confidence interval [CI] 1.3-2.7; P < 0.0005) for K103N, 4.4-fold (95% CI 1.2-16.6; P = 0.026) for Y181C, 4.8-fold (95% CI 1.5-15.1; P = 0.008) for L90M and 8.7-fold (95% CI 4.0-18.6; P < 0.0005) for M184V. We found no relationship between AS-PCR assay sensitivity and frequency of additional mutation detection. CONCLUSIONS: Additional detection of drug resistance mutations using AS-PCR minority mutation assays vary significantly depending on the mutation examined; however, the most marked increase in detection of resistance mutations was observed for M184V, a mutation seldom detected by standard techniques in drug-naive patients. We suggest that the presence of drug resistance mutations can be more accurately estimated using a combination of AS-PCR and standard genotyping.
Authors: Seble G Kassaye; Zehava Grossman; Maya Balamane; Betsy Johnston-White; Chenglong Liu; Princy Kumar; Mary Young; Michael C Sneller; Irini Sereti; Robin Dewar; Catherine Rehm; William Meyer; Robert Shafer; David Katzenstein; Frank Maldarelli Journal: Clin Infect Dis Date: 2016-06-15 Impact factor: 9.079
Authors: Matthew McCallum; Maureen Oliveira; Ruxandra-Ilinca Ibanescu; Victor G Kramer; Daniela Moisi; Eugene L Asahchop; Bluma G Brenner; P Richard Harrigan; Hongtao Xu; Mark A Wainberg Journal: Antimicrob Agents Chemother Date: 2013-07-15 Impact factor: 5.191
Authors: Amin S Hassan; David F Bibby; Shalton M Mwaringa; Clara A Agutu; Kennedy K Ndirangu; Eduard J Sanders; Patricia A Cane; Jean L Mbisa; James A Berkley Journal: PLoS One Date: 2019-02-13 Impact factor: 3.240
Authors: Mary F Kearney; Jonathan Spindler; Ann Wiegand; Wei Shao; Richard Haubrich; Sharon Riddler; Christina M Lalama; Michael D Hughes; John M Coffin; John W Mellors Journal: PLoS One Date: 2018-01-25 Impact factor: 3.240