A phylotype-based analysis highlights the role of drug-naive HIV-positive individuals in the transmission of antiretroviral resistance in the UK.

Raphaël Mourad; François Chevennet; David T Dunn; Esther Fearnhill; Valerie Delpech; David Asboe; Olivier Gascuel; Stéphane Hue; UK HIV Drug Resistance Database & the Collaborative HIV, Anti-HI; (2015) A phylotype-based analysis highlights the role of drug-naive HIV-positive individuals in the transmission of antiretroviral resistance in the UK. AIDS (London, England), 29 (15). pp. 1917-1925. ISSN 0269-9370 DOI: 10.1097/QAD.0000000000000768
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OBJECTIVE: Antiretroviral-naive HIV-positive individuals contribute to the transmission of drug-resistant viruses, compromising first-line therapy. Using phylogenetic inference, we quantified the proportion of transmitted drug-resistance originating from a treatment-naive source. METHODS: Using a novel phylotype-based approach, 24 550 HIV-1 subtype B partial pol gene sequences from the UK HIV Drug Resistance database were analysed. Ongoing transmission of drug resistance amongst HIV-positive individuals was identified as phylotypes of at least three sequences with at least one shared drug resistance mutation, a maximum intra-clade genetic distance of 4.0% and a basal branch support at least 90%. The time of persistence of the transmission chains was estimated using a fast least-squares molecular clock inference approach. RESULTS: Around 70% of transmitted drug-resistance had a treatment-naive source. The most commonly transmitted mutations were L90M in the protease gene and K103N, T215D and T215S in reverse transcriptase. Reversion to wild type occurred at a low frequency and drug-independent reservoirs of resistance have persisted for up to 13 years. CONCLUSION: These results illustrate the impact of viral fitness on the establishment of resistance reservoirs and support the notion that earlier diagnoses and treatment of HIV infections are warranted for counteracting the spread of antiretroviral resistance. Phylotype-based phylogenetic inference is an attractive approach for the routine surveillance of transmitted drug resistance in HIV as well as in other pathogens for which genotypic resistance data are available.

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