ReviewViruses2026
Temporal Evolution of Drug Resistance to HIV Integrase Inhibitors.
Review in Viruses, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
6 authors.
Funding
Abstract
HIV-1 integrase (IN) strand transfer inhibitors (INSTIs) are central to modern antiretroviral therapy (ART) because of their high potency and durable effect on viral suppression. However, drug resistance mutations (DRMs) within HIV-1 IN emerge, which can compromise long-term treatment efficacy. Many distinct DRMs that arise under INSTI therapy have been extensively tabulated in public repositories and literature. However, the timelines over which they emerge, accumulate, and consolidate in patients have not been systematically integrated across clinical and experimental studies. In this review, we synthesize current evidence on the temporal evolution of DRMs within HIV-1 IN by examining mutational kinetic data from viruses derived from people living with HIV/AIDS (PLWH) and from in vitro selection experiments. We compare experimental timelines to recent computational predictions derived from Potts-based fitness landscapes coupled with kinetic Monte Carlo simulations and identify reproducible kinetic classes that distinguish fast-, intermediate-, and slow-emerging DRMs. Rapidly emerging DRMs such as E92Q and N155H typically appear early under drug pressure and often represent low-barrier adaptive responses, whereas the most clinically consequential mutations, such as Q148H/K/R, G140A/S, and E138K, arise only after extended therapy and generally require compensatory mutational backgrounds to persist. Although absolute emergence times vary substantially between in vivo and in vitro systems, consistent temporal trends across datasets support the existence of underlying epistatic constraints that shape drug resistance evolution. Understanding DRM timelines is clinically relevant because it provides a framework for interpreting resistance detected at virological failure, informs optimal timing of resistance testing, and may enable earlier identification of high-risk evolutionary trajectories before durable resistance is established.
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