Background. Human immunodeficiency virus (HIV)-1 drug resistance mutations (DRMs) often accompany treatment failure. Although subtype differences are widely studied, DRM comparisons between subtypes either focus on specific geographic regions or include populations with heterogeneous treatments. Methods. We characterized DRM patterns following first-line failure and their impact on future treatment in a global, multi-subtype reverse-transcriptase sequence dataset. We developed a hierarchical modeling approach to address the high-dimensional challenge of modeling and comparing frequencies of multiple DRMs in varying first-line regimens, durations, and subtypes. Drug resistance mutation co-occurrence was characterized using a novel application of a statistical network model. Results. In 1425 sequences, 202 subtype B, 696 C, 44 G, 351 circulating recombinant forms (CRF)01_AE, 58 CRF02_AG, and 74 from other subtypes mutation frequencies were higher in subtypes C and CRF01_AE compared with B overall. Mutation frequency increased by 9%-20% at reverse transcriptase positions 41, 67, 70, 184, 215, and 219 in subtype C and CRF01_AE vs B. Subtype C and CRF01_AE exhibited higher predicted cross-resistance (+12%-18%) to future therapy options compared with subtype B. Topologies of subtype mutation networks were mostly similar. Conclusions. We find clear differences in DRM outcomes following first-line failure, suggesting subtype-specific ecological or biological factors that determine DRM patterns.
Keywords: HIV; drug resistance; evolution; first-line; subtype.