ArticlePLoS pathogens2026
Extensive diversity and impact of drug-resistant HIV-1 variants in individuals with prior virologic failure.
Article in PLoS pathogens, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
HIV-1 drug resistance remains a major challenge to treatment and control efforts, particularly in sub-Saharan Africa (sSA). However, standard resistance genotyping does not adequately capture linked drug resistance mutations within the viral quasispecies that may influence virologic failure (VF). We used a next-generation sequencing primer ID (NGS-Primer ID) assay to characterize linked HIV-1 drug resistance mutations in plasma from participants in the Resistance Testing to Improve Management of Virologic Failure (REVAMP) study who had detectable viremia on first-line non-nucleoside reverse transcriptase inhibitor (NNRTI)-based antiretroviral therapy (ART) and were maintained on NNRTI-based regimens. For each participant, we calculated a weighted genotypic susceptibility score (wGSS) based on the GSS of each reported pattern and its sequence-supported frequency within the sample. Plasma specimens from 108 participants were sequenced. Sanger sequencing showed a median GSS of 1.0 (IQR, 1.0-2.0), whereas NGS-Primer ID identified a median of 10 distinct resistance patterns per participant (IQR, 5-17), with 67% (IQR, 8-92) of reported DRM-pattern frequency within participants corresponding to linked dual-class mutations. A broad spectrum of drug-susceptible and resistant- DRM patterns were observed, with the median difference between the highest and lowest pattern-specific GSS being 2.0 (2.0-2.75). Within each participant, a median of 10% of reported patterns showed less resistance, while 19% showed more resistance compared to that predicted by Sanger sequencing. Individuals with persistent VF had significantly lower wGSS at study entry than those who later achieved virologic re-suppression (median, 1.3 vs 2.1; p < 0.001). NGS-Primer ID revealed substantial intra-host diversity in linked HIV-1 drug resistance patterns that was not captured by conventional Sanger sequencing. Incorporating linked resistance patterns into susceptibility assessment may improve prediction of subsequent virologic failure.
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