Discordance between Etravirine Phenotype and Genotype-Based Predicted Phenotype for Subtype C HIV-1 from First-Line Antiretroviral Therapy Failures in South Africa

Publication: Antimicrobial Agents and Chemotherapy


Etravirine (ETR) is a non-nucleoside reverse transcriptase inhibitor (NNRTI) used in treatment-experienced individuals. Genotypic resistance test-interpretation systems can predict ETR resistance; however, genotype-based algorithms are derived primarily from HIV-1 subtype B and may not accurately predict resistance in non-B subtypes. The frequency of ETR resistance among recombinant subtype C HIV-1 and accuracy of genotypic interpretation systems were investigated. Methods: HIV-1 LAI containing full-length RT from HIV-1 subtype C-positive individuals experiencing virologic failure (>10,000 copies/ml and >1 NNRTI-resistance associated mutation) were phenotyped for ETR susceptibility. Fold-change (FC) was calculated against a composite EC 50 from treatment-naïve individuals and three classifications were assigned: <2.9-FC susceptible, ≥2.9-10-FC partially-resistant and >10-FC fully-resistant. The Stanford HIVdb-v8.4 was used for genotype predictions merging the susceptible/potential low-level and low-level/intermediate groups for 3×3 comparison. Results: Fifty-four of 100 samples had reduced ETR susceptibility (≥2.9-FC). The FC correlated with HIVdb-v8.4 (Spearman’s rho=0.62; p<0.0001); however, 44% of samples were partially (1 resistance classification difference) and 4% completely discordant (2 resistance classification differences). Of the 34 samples with FC>10, 26 were HIVdb-v8.4 classified as low-intermediate resistant. L100I, Y181C or M230L were present in 27/34 (79%) of samples with FC>10 but only in 2/46 (4%) of samples with FC<2.9. No other mutations were associated with ETR resistance. Viruses containing K65R were associated with reduced ETR susceptibility, but 65R reversions did not increase ETR susceptibility. Conclusion: Genotypic interpretation systems were found to misclassify ETR susceptibility in HIV-1 subtype C samples. Modifications to genotypic algorithms are needed to improve the prediction of ETR resistance for HIV-1 subtype C.

By Kevin Dylan McCormick, Kerri J Penrose, Chanson J Brumme, P. Richard Harrigan, Raquel V. Viana, John, W. Mellors, Urvi M. Parikh, Carole L. Wallis