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. 2023 Feb 23;18(2):e0281528.
doi: 10.1371/journal.pone.0281528. eCollection 2023.

HIV virologic response, patterns of drug resistance mutations and correlates among adolescents and young adults: A cross-sectional study in Tanzania

Joan Rugemalila  1   2 , Doreen Kamori  1 , Peter Kunambi  1 , Mucho Mizinduko  1 , Amon Sabasaba  1 , Salim Masoud  1 , Frank Msafiri  1 , Sabina Mugusi  1 , Rita Mutagonda  1 , Linda Mlunde  1 , Davis Amani  1 , Erick Mboya  1 , Macdonald Mahiti  1 , George Ruhago  1 , Jeremiah Mushi  3 , Veryeh Sambu  3 , George Mgomella  4 , Boniface Jullu  5 , Werner Maokola  3 , Prosper Njau  3 , Beatrice Mutayoba  3 , Godfrey Barabona  6 , Takamasa Ueno  6 , Andrea Pembe  1 , Tumaini Nagu  1 , Bruno Sunguya  1   6 , Said Aboud  1
Affiliations

HIV virologic response, patterns of drug resistance mutations and correlates among adolescents and young adults: A cross-sectional study in Tanzania

Joan Rugemalila et al. PLoS One. .

Abstract

Background: The emergence of HIV drug resistance mutations (DRMs) is of significant threat to achieving viral suppression (VS) in the quest to achieve global elimination targets. We hereby report virologic outcomes and patterns of acquired DRMs and its associated factors among adolescents and young adults (AYA) from a broader HIV drug resistance surveillance conducted in Tanzania.

Methods: Data of AYA was extracted from a cross-sectional study conducted in 36 selected facilities using a two-stage cluster sampling design. Dried blood spot (DBS) samples were collected and samples with a viral load (VL) ≥1000 copies/mL underwent genotyping for the HIV-1 pol gene. Stanford HIV database algorithm predicted acquired DRMs, Fisher's exact test and multivariable logistic regression assessed factors associated with DRMs and VS, respectively.

Findings: We analyzed data of 578 AYA on antiretroviral therapy (ART) for 9-15 and ≥ 36 months; among them, 91.5% and 88.2% had VS (VL<1000copies/mL) at early and late time points, respectively. Genotyping of 64 participants (11.2%) who had VL ≥1000 copies/ml detected 71.9% of any DRM. Clinically relevant DRMs were K103N, M184V, M41L, T215Y/F, L210W/L, K70R, D67N, L89V/T, G118R, E138K, T66A, T97A and unexpectedly absent K65R. Participants on a protease inhibitor (PI) based regimen were twice as likely to not achieve VS compared to those on integrase strand transfer inhibitors (INSTI). The initial VL done 6 months after ART initiation of ≥1000copies/mL was the primary factor associated with detecting DRMs (p = .019).

Conclusions: VS amongst AYA is lower than the third UNAIDs target. Additionally, a high prevalence of ADR and high levels of circulating clinically relevant DRMs may compromise the long-term VS in AYA. Furthermore, the first VL result of ≥1000copies/ml after ART initiation is a significant risk factor for developing DRMs. Thus, strict VL monitoring for early identification of treatment failure and genotypic testing during any ART switch is recommended to improve treatment outcomes for AYA.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flow chart showing enrollment of study participants, viral load and genotypic testing.
Fig 2
Fig 2. The proportion of drug-resistant mutations selected by antiretroviral drug classes among adolescents and young adults.
Fig 3
Fig 3. The proportion of drug-resistance mutations selected by ARV classes showing dual and triple class resistance among adolescents and young adults.
Fig 4
Fig 4. The proportion of drug-resistant mutations selected by non-nucleoside reverse transcriptase inhibitors among adolescents and young adults.
Fig 5
Fig 5. The proportion of drug-resistant mutations selected by the nucleoside reverse transcriptase inhibitors among adolescents and young adults.
Fig 6
Fig 6. The proportion of drug-resistant mutations selected by protease inhibitors among adolescents and young adults.
Fig 7
Fig 7. The proportion of drug-resistant mutations selected by integrase strand transfer inhibitors among adolescents and young adults.
Fig 8
Fig 8. Phylogenetic tree illustrating the distribution of HIV-1 subtypes among participants with high viremia.
See this image and copyright information in PMC

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