HIV-1 resistance mutations and genetic diversity

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Introduction

The issue of antiretroviral resistance in HIV-infected children is still topical, particularly because of its impact on the mortality and morbidity associated with this infection in this segment of the population [1]. At the end of 2022, of the 1.5 million children living with HIV worldwide, 57% had access to treatment [2]. Despite several advancements, it may be difficult to achieve the second UNAIDS target, which stipulates that 95% of HIV-infected people should be on antiretroviral treatment [3,4]. The widespread use of antiretroviral therapy (ART), particularly programs to prevent mother-to-child transmission has led to a 58% reduction in new infections among children. However, suboptimal antiretroviral therapy in mothers, antiretroviral prophylaxis and difficulties in administering treatment in newborns strongly contribute to the development of treatment resistance especially in the African context [5,6]. This selection of resistance mutations inevitably leads to the failure of antiretroviral therapy [7]. Regular follow-up of these children by quantifying the viral load makes it possible to anticipate virological failure and avoid an accumulation of resistance mutations [8].

HIV prevalence in the general population is 0.8% in Benin [9,10]. The ART program started in 2005 in the country and according to the 2021 monitoring report, around 2,392 children are living with HIV, of whom 2,383 are on antiretroviral treatment[11]. According to the national policy, ART must be initiated in all children living with HIV, regardless of T cell count (CD4+T cells) and clinical stage. Considerable progress has been made in biological and therapeutic care. Indeed, in terms of biological care, the operational capacity of laboratories has been increased through the acquisition and provision of molecular biology equipment for the realization of viral load and genotyping. This strategy has made it possible to increase national coverage by offering these services to the greatest number of patients. Therapeutic management has been improved thanks to certain actions, including introducing more effective and better-tolerated molecules such as Dolutegravir in therapeutic regimens, organizing consultation workshops, and sharing experiences and good practices of the actors involved (prescribing doctors or nurses). According to the national guidelines for the therapeutic management of HIV infection and contained in the document of national HIV standards and policies, the treatment regimens in force in Benin for the treatment of children are made up of 2NRTI+1NNRTI/PI/INSTI. Thus several combinations are possible, namely: ((ABC/ AZT) + 3TC + (DTG/ LPV/r/ EFV)) (Abacavir/Zidovudine + Lamivudine + Dolutegravir/lopinavir boosted by Ritonavir/ Efavirenz) or ((TDF/ AZT) + 3TC + (DTG/ EFV)) (Tenofovir/Zidovudine + Lamivudine + Dolutegravir/Efavirenz). Those therapeutic lines are based on the child’s weight which is less than or more than 30 kg without forgetting iron supplementation when using DTG [12]. Biological monitoring of the effectiveness of antiretroviral therapy in a resource-limited country context is mainly based on TCD4+ lymphocyte counts and plasma viral load quantification every 6 months [12]. The challenge in pediatric care in our country remains the maintenance of efficient ART despite the difficulties of compliance and the emergence of drug resistance described. The issue of pediatric antiretroviral resistance in Benin remains alarmingly underexplored, exposing a gap that needs to be addressed. However, a study conducted in 2018 at the pediatric clinic of the National University Hospital Center in Cotonou revealed a high frequency of resistance to at least one antiretroviral in children on both first-line (39/45; 87%) and second-line (7/8; 88%) regimens [13]. Since this study, efforts have been made in the training of doctors and psychologists responsible for the care of infected children under ART in Benin. Surveillance of antiretroviral resistance is important not only to guide treatment guidelines but also to explore the role of routine genotypic testing in the biological monitoring of children.

This study was conducted in five pediatric facilities care in Benin and has the main objective of presenting the frequency of HIV-1 resistance mutations associated with ART and genetic diversity in children with virological failure.

Methods

Study population

A cross-sectional study was carried out from November 20, 2020, to November 30, 2022, in children under 15 years of age who had ART failed (VL > 3log₁₀) at five facilities care in the country: Abomey-Calavi Hospital, a non-governmental organization (NGO) Racines, Bethesda Hospital, University Hospital Center for Mothers and Children (CHU-MEL) and Suru-Léré Hospital sites. The recruitment of participants was carried out from November 20, 2020, to October 15, 2021. The sequencing, data collection and analysis were done from October 20, 2021 to November 30, 2022.

Blood samples

Whole blood samples were collected in EDTA tubes from all eligible participants. Plasma aliquots were taken and stored at -80°C.

Viral load testing

Plasma HIV-1 RNA viral load (VL) was performed using Abbott RealTime HIV-1 assay (Abbott Molecular, Inc) in the National Reference Laboratory Fighting Against AIDS in Benin (NRL/PSLS). The linear range of 40–10.000.000 copies/ml with a detection limit of 40 copies/ml was defined by the manufacturers [14].

Drug resistance genotyping

PCR and genotyping of HIV-1 drug resistance were performed using the Viroseq HIV-1 v2.0 Genotyping Kit, as previously described according to the manufacturer’s instructions [15]. This kit is a complete package of the necessary reagents from RNA extraction to sequencing reactions. This technique amplifies the entire (amino acids 1–99) of the protease (Pr) gene and 2/3 (amino acid 1–335) of the reverse transcriptase (RT) using seven primers (A, B, C, D, F, G, H) to generate a 1.8kb PCR product. This amplicon was used as a sequencing template to generate approximately 1.3 kb of consensus sequence. This pol gene region of the HIV-1 fragments was subjected to Applied Biosystems’ ABI 3500 genetic analyser. The consensus sequences were assembled and analyzed by the Viroseq HIV-1 V2.5 377 software to identify mutations compared to an HXB2 reference sequence of the B subtype (GenBank accession number K03455).

Genotypic resistance profiles were obtained by submitting the sequences to the HIV drug resistance database at Stanford University (https://hivdb.stanford.edu/).

Phylogenetic analysis

Nucleotide sequences were aligned with a set of reference sequences representative of HIV-1 group M subtypes and Circulating Recombinant Forms (CRFs) in West and Central Africa with three reference sequences per subtype/CRF. Sequences were aligned using MAFFT version 7 (https://mafft.cbrc.jp/alignment/server/). Gap positions were removed under AliView. Each sample sequence was submitted a similarity plot analysis with SimPlot v3.5.1 from the alignment [16]. For recombinant profiles, individual bootscan analyses were performed using the Kimura two-parameter model with a window of 350 bp advancing in 20 bp increments, and the alignment was cut into several segments as defined by the bootscan plot. Each segment was submitted to a Maximum Likelihood (ML) phylogenetic analysis to confirm the subtype/CRF designation [17]. The final alignment was drawn keeping all HIV-1/M subtypes and the sub-subtypes and CRFs within the new sample sequences. The final tree was drawn under GTR+F+R4 as the best-fit model of nucleotide substitution according to BIC and 1000 bootstrap resampling, by using IQ-Tree v1.6.12 server (http://iqtree.cibiv.univie.ac.at). The consensus tree was edited with FigTree v1.4.4.

Recent transmission clusters were ascertained based on short branch lengths (≤ 0.015) and high support values (>98%).

The newly generated sequences were submitted to Genbank under accession numbers: OR139618 to OR139649.

Statistical analysis

Data on sociodemographic characteristics and treatment history were collected from participants’ medical records using a questionnaire. All data were entered into Excel 2016 and analyzed with this software. A descriptive analysis was carried out, with data presented in the form of numbers, percentages, mean, interquartile range, and median with their 95% confidence intervals.

Ethics approval and confidentiality

The protocol was also approved by the National Ethics Committee for Health Research (CNERS) under trial number 30 of August 30, 2020 (Reference N°: 111/MS/DRFMT/CNERS/SA).

Written informed consent was obtained from the parents or legal guardians of the participants involved in the study. Confidentiality and anonymity of the information was also maintained. The study was conducted using the relevant guidelines and regulations.

Results

Patient characteristics

Forty-seven cases with a viral load greater than 3log₁₀ copies/ml were included in this study for genotyping. Their median age was 120 [Interquartile Range 90–144] months and they were predominantly female (26/47; 55.3%). The most common treatment used was a regimen based on EFV (22/47; 46.8%). The mean CD4+T cells count was 760.4 with a median of 603 [Interquartile Range 366.5–1021.5] cells/μl blood. The mean viral load was 4.43 log₁₀ and, the median was 4.39 [Interquartile Range 3.81–4.86 log₁₀] copies/ml. Table 1 describes the demographic characteristics, biological data (VL), and DRMs among children included in the study.

[Figure omitted. See PDF.]

Resistance mutations

Sequencing of HIV-1 gene Pol was successful among (37/47; 78.72%) children. Resistance mutations were detected in (32/37; 86.48%) and (29/32; 90.62%) had at least one surveillance drug resistance associated mutation. Of these, approximately (25/32; 78.12%), (28/32; 87.5%), (4/32; 12.90%), (22/32; 68.75%), (02/32; 6.25%) had at least one resistance mutation associated with NRTIs, NNRTIs, PIs, NNRTIs+NRTIs, and NNRTIs+NRTIs+PIs respectively. (12/32; 37.5%) of children carried mutations associated with TAMs (Thymidine Analog Mutations) including TAMsI (M41L, L210W, and T215Y) and TAMsII (D67N, K70R, T215F, and K219Q/E).

Among mutations associated to NRTIs, TAMs represented (20/62; 32.2%) followed by M184V (21/62; 33.9%) and T69G/D (2/62; 3.2%). Others NRTIs associated mutations were present (19/62; 30.7%) (Fig 1A). K103N represents (18/64; 28.1%) among mutations associated with NNRTIs followed by P225H (7/64; 10.9%). Other NNRTIs encountered are presented in Fig 1B.

[Figure omitted. See PDF.]

A) NRTIs resistance associated mutation prevalence, B) NNRTIs resistance associated mutations prevalence, C) PIs resistance associated mutations prevalence.

The major PIs associated mutation, I54V (3/6; 50%) observed is presented in Fig 1C. Some PIs accessory mutations were observed, such as K20T, L89IV and Q58E (respectively 1/3; 33.33%).

Distribution of 32 HIV‑1 group M variants among children in Benin

A predominance of CRF02_AG (72%, 23/32) was observed in this population, followed by unique recombinant forms (URFs) (25%, 8/32). One sequence harbored pure subtype G (3.12%, 1/32). Among unique recombinants, two sequences (4183 and 13193) were segregated into one recent transmission chain.

The phylogenetic tree is presented in Fig 2.

[Figure omitted. See PDF.]

Phylogeny was inferred under IQ-Tree version 1.6.12 by maximum likelihood for 1302 unambiguously aligned nucleotide sequences of protease and partial reverse transcriptase genes for 32 samples from the study with 1000 bootstrap resampling under GTR+F+R4 as the best-fit model of nucleotide substitution according to BIC. The consensus tree was edited with FigTree v1.4.4. HIV-1 reference sequences are in black, the new sequences from the study are in red. Branch supports are indicated for the main clades. Asterisks refer to unique recombinant strains.

The characterization of the recombinants by bootscanning allowed us to identify the sequences of three samples as CFR02_AG/A3, two as CRF02/A, one CRF02_AG/G/CRF02_AG, one A3/U/A3, and one G/CRF02/CRF43. The bootscans of recombinant forms are presented in Figs 3–8.

[Figure omitted. See PDF.]

The bootscan analysis was performed using SimPlot software with a 350 bp window and a 20 bp step. The x-axis represents the position of the nucleotides in alignment. The different clades of HIV-1 are represented by specific color codes.

[Figure omitted. See PDF.]

Discussion

This study reported the frequency of antiretroviral resistance in a population of children with virological failure and followed up at five treatment sites in Benin. Most participants did not have an immune deficiency as defined by the WHO pediatric antiretroviral treatment guidelines (median CD4 count of 603 cells/μl). Viral loads, although high with a median of 4.39 log₁₀ (24,547 copies/ml), were not able to obtain optimal performance during sequencing because there was about 21.28% PCR failure. Knowing that the detection sensitivity of the Viroseq technique is 2,000 copies/ml, the sequencing failure rate in the present study can be partly justified by the fact that approximately 12.77% of the participants had a viral load less than 2,000 copies/ml (3.30log₁₀). In addition, sequencing failures related to the Viroseq technique have been reported in the literature. Indeed, it would seem that the performance of this technique is altered by the sequence variations of the non-B subtypes [18–20]. The Viroseq technique was developed for subtype B, which circulates mainly in northern countries, but the predominant subtype in West Africa is the non-B subtype.

The frequency of antiretroviral resistance among participants in this study was 86.48% with 87.5%, 78.12%, and 12.90% mutations in NNRTIs, NRTIs and PIs, respectively. The frequency of dual-class mutations was significant (68.75%) and 02 participants harboured triple-class mutations. These high rates of mutations observed could be justified by the relatively long duration of antiretroviral use in the participants in this study, which averaged 54 months. Although the size of the samples differs. The results are superimposed on those obtained at the Hubert Maga University Hospital Center which was called National University Hospital Center in 2018 which reported 71%, 84%, and 65% resistance to NNRTI and double-class NRTIs respectively [13]. However, no resistance to PIs was found in the study in children on first-line treatment. This difference in PI resistance in the two studies may be explained by the larger number of participants on PI treatment in the present study (20 versus 12). Similar frequencies have also been reported in some African countries such as Senegal [21], Ethiopia [22], Tanzania [23] and Rwanda [24]. The high frequency of dual-class resistance observed in participants in this study strongly compromises future treatment options in these participants, particularly in the two children who harboured triple-class resistance NRTI+NNRTI+PI. Children who are likely to have been exposed to antiretrovirals used in the prevention of mother-to-child transmission (PMTCT) program. It will therefore be necessary to explore and implement other combinations that are more efficient for these participants.

As in most studies conducted in Africa and elsewhere, the M184V mutation is the most prevalent in the NRTI class [25–27]. This mutation confers high-level resistance to Lamivudine and Emtricitabine but also low/intermediate resistance to Abacavir. It should be noted, however, that this same mutation increases susceptibility to Zidovudine and Tenofovir [28,29]. Among the participants, 37.5% (12/32) selected TAMs with as many type I as type II TAMs. Similar results have been reported in Cameroon [30]. These mutations greatly reduce viral susceptibility to zidovudine [31]. In this case, the selection for this mutation is probably due to the high use of zidovudine in the prevention of mother-to-child transmission program. On the other hand, it has been reported that in the case of subtype C, the combination of M184V and TAMs significantly increased susceptibility to Zidovudine [32].

In the NNRTI class, there is a prevalence of K103N (18/64, 28.1%) and P225H (7/64, 10.9%) which confer resistance to nevirapine and Efavirenz and therefore compromises the use of these two drugs in these participants. Indeed, these mutations are selected in the event of exposure to these two molecules or the event of suboptimal treatment due to poor compliance [33,34]. Similar results were obtained in other contexts [23,35]. In addition, NNRTI-associated V106A, Y188L, and P225H mutations confer cross-resistance to Rilpivirine, Etravirine, and Doravirine [36]. These molecules have never been used in treatment protocols in Benin.

PI mutations were observed in four participants, two of whom had intermediate resistance to Atazanavir and the remaining two had low-level resistance to the same drug. As this drug is used in adult alternative treatment lines, the presence of this mutation suggests the mother’s transmitted resistance. The most common mutation found in participants is I54V, a polymorphic mutation that reduces susceptibility to almost all PIs except boosted Darunavir (DRV/r). The gradual replacement of NRTIs with integrase inhibitors (INSTIs) in treatment protocols in Benin is expected to improve the management of these participants.

The genetic diversity in the population studied is characterized by the pure G subtype (3.12%, 1/32) and a predominance of recombinant forms with the most preponderant CRF02_AG (72%, 23/32). CRF02_AG is the most isolated recombinant form in West Africa [37]. This finding is corroborated by observations made at the pediatric clinic of the HKM University Hospital in Cotonou and in treatment-naïve adults [11,38]. The errors of RT and the high replication capacity of HIV generate very diverse viral variants, sometimes even within the same individual [39]. This multitude of viral variants is responsible for the scale of the epidemic and the complexity of management. Among them, the recombinant forms of UFRs and CRFs in particular represent the vast majority of the genetic diversity of HIV [40]. Among the UFRs identified in a non-negligible proportion (25%, 8/32), several derive from clades that circulate in the West African sub-region: Senegal, South Africa, Nigeria, and Cameroon as indicated by the different phylogenetic trees. The presence of URFs suggests that children were born to mothers infected with more than one virus strain as previously described in the country [41].

The presence of the recombinant G/CRF02/CRF43 could be explained by migratory flows linked to trade between Saudi Arabia and Benin, but the border proximity with Nigeria seems more likely because recombinant forms have been identified in a higher proportion (16%) in this country. Indeed, although the recombinant CRF43_02G was described for the first time in Saudi Arabia, estimates of its appearance in Nigeria date back to 1971 (95% HPD: 1952–1983) [42]. The recombinant CRF02_AG/A3 has been previously isolated from Senegal and is associated with a faster progression to the AIDS stage and a high proportion of death [43,44]. The A3 sub-subtype is circulating in some neighbouring countries such as Senegal, Niger, Nigeria, and Ivory Coast [45]. The recombinants identified in this study could come from the mosaic of variants previously described in Benin and the sub-region [46]. Regarding the transmission cluster, there does not seem to be any epidemiological data suggesting they have family ties. Indeed, although these two samples were obtained in the same department, these participants were enrolled in different health facilities care. For the confidentiality of data relating to the participants’ informed consent, we could not request additional information to explain this transmission cluster.

Limitations

The major limitation of our study is the small sample size. Another important limitation is the unavailability of in-house genotyping kits to retest samples that have failed genotyping. In addition, it would also have been interesting to investigate the two sequences resulting from a recent chain of transmission. Also, it would be desirable to evaluate the prevalence of resistance to antiretroviral, particularly to integrase strand transfer inhibitors, in a larger cohort of children. In the current context of widespread use of this therapeutic class, monitoring resistance is proving to be a necessity to help programs ensure optimal treatment for all.

Conclusion

The prevalence of antiretroviral resistance is high in the study population, highlighting the importance of switching to antiretroviral with a high genetic barrier, such as Dolutegravir, in pediatric treatment. The generalization of the use of integrase strand transfer inhibitors is a solution to which prevention and resistance monitoring actions must be associated as recommended by the WHO to guarantee a better quality of life for children under treatment.

Supporting information

S1 File.

https://doi.org/10.1371/journal.pone.0317882.s001

(XLSX)

S1 Questionnaire.

https://doi.org/10.1371/journal.pone.0317882.s002

(DOCX)

Acknowledgments

We thank the Ministry of Health and the AIDS Control Program of Benin. We also thank the heads of the paediatric departments who spared no effort to ensure the children’s participation. We want to thank the biologists of the National Reference Laboratory for their availability.

References

1. 1. Koay WLA, Kose-Otieno J, Rakhmanina N. HIV Drug Resistance in Children and Adolescents: Always a Challenge? Curr Epidemiol Rep. 1 sept 2021;8(3):97‑107. pmid:33758743

* View Article

* PubMed/NCBI

* Google Scholar

2. 2. UNAIDS. https://www.unaids.org/sites/default/files/media_asset/UNAIDS_FactSheet_en.pdf. 2013. 2013;

3. 3. Djiyou ABD, Penda CI, Madec Y, Ngondi GD, Moukoko A, Varloteaux M, et al. Viral load suppression in HIV-infected adolescents in cameroon: towards achieving the UNAIDS 95% viral suppression target. BMC Pediatrics. 15 mars 2023;23(1):119. pmid:36922769

* View Article

* PubMed/NCBI

* Google Scholar

4. 4. Frescura L, Godfrey-Faussett P, Feizzadeh A A, El-Sadr W, Syarif O, Ghys PD, et al. Achieving the 95 95 95 targets for all: A pathway to ending AIDS. PLoS One. 2022;17(8):e0272405. pmid:35925943

* View Article

* PubMed/NCBI

* Google Scholar

5. 5. Siberry GK, Amzel A, Ramos A, Rivadeneira ED. Impact of Human Immunodeficiency Virus Drug Resistance on Treatment of Human Immunodeficiency Virus Infection in Children in Low- and Middle-Income Countries. The Journal of Infectious Diseases. 1 déc 2017;216(suppl_9):S838‑42. pmid:29045697

* View Article

* PubMed/NCBI

* Google Scholar

6. 6. Mengesha MM, Embibel M, Gobena T, Tunje A, Jerene D, Hallström IK. Antiretroviral therapy non-adherence among children living with HIV in Dire Dawa, Eastern Ethiopia: a case-control study. BMC Pediatr. déc 2022;22(1):1‑11. pmid:36357856

* View Article

* PubMed/NCBI

* Google Scholar

7. 7. Rojas Sánchez P, Domínguez S, Jiménez De Ory S, Prieto L, Rojo P, Mellado P, et al. Trends in Drug Resistance Prevalence, HIV-1 Variants and Clinical Status in HIV-1-infected Pediatric Population in Madrid: 1993 to 2015 Analysis. Pediatr Infect Dis J. mars 2018;37(3):e48‑57. pmid:28991889

* View Article

* PubMed/NCBI

* Google Scholar

8. 8. Boender TS, Kityo CM, Boerma RS, Hamers RL, Ondoa P, Wellington M, et al. Accumulation of HIV-1 drug resistance after continued virological failure on first-line ART in adults and children in sub-Saharan Africa. J Antimicrob Chemother. 1 oct 2016;71(10):2918‑27. pmid:27342546

* View Article

* PubMed/NCBI

* Google Scholar

9. 9. Diabaté S, Behanzin L, Guédou F, Olodo M, Goma-Matsetse AE, Aza-Gnandji M, et al. Prevalence and determinants of high-risk human papilloma virus among men who have sex with men in Benin: a cross-sectional study embedded in a demonstration project on pre-exposure prophylaxis against HIV. BMJ Open. 6 nov 2023;13(11):e074464. pmid:37931972

* View Article

* PubMed/NCBI

* Google Scholar

10. 10. UNAIDS. UNAIDS Data 2021. Geneva: UNAIDS, 2021. Available: https://wwwunaidsorg/sites/default/files/media_asset/JC3032_AIDS_Data_book_2021_En.pdf. 2021;

11. 11. Politique-Normes-et-Procedures-de-PEC-des-IST-au-BENIN-2018.pdf [Internet]. [cité 25 oct 2024]. Disponible sur: https://psls.bj/wp-content/uploads/2023/12/Politique-Normes-et-Procedures-de-PEC-des-IST-au-BENIN-2018.pdf

12. 12. MS/PSLS/BENIN. Politique, Normes et Procédures de Prise en Charge des Personnes Vivant avec le VIH au Bénin. 2019.

13. 13. Fofana DB, d’Almeida M, Lambert-Niclot S, Peytavin G, Girard PM, Lafia B, et al. Resistance profile and treatment outcomes in HIV-infected children at virological failure in Benin, West Africa. J Antimicrob Chemother. 1 nov 2018;73(11):3143‑7. pmid:30060186

* View Article

* PubMed/NCBI

* Google Scholar

14. 14. Pronier C, Boukthir S, Courtellemont L, Lagathu G, Maillard A, Thibault V. Performance comparison of new Veris and Xpert random access HIV-1 RNA quantification assays. Virology Journal. 11 oct 2018;15(1):156. pmid:30305133

* View Article

* PubMed/NCBI

* Google Scholar

15. 15. Thiam M, Diop-Ndiaye H, Kebe K, Vidal N, Diakhate-Lô R, Diouara AAM, et al. Performance of the ViroSeq HIV-1 genotyping system v2.0 on HIV-1 strains circulating in Senegal. J Virol Methods. mars 2013;188(1‑2):97‑103. pmid:23266258

* View Article

* PubMed/NCBI

* Google Scholar

16. 16. Lole Kavita S., Bollinger Robert C., Paranjape Ramesh S., Gadkari Deepak, Kulkarni Smita S., Novak Nicole G., et al. Full-Length Human Immunodeficiency Virus Type 1 Genomes from Subtype C-Infected Seroconverters in India, with Evidence of Intersubtype Recombination | Journal of Virology [Internet]. [cité 5 déc 2024]. Disponible sur: https://login.research4life.org/tacsgr1journals_asm_org/doi/10.1128/jvi.73.1.152-160.1999

* View Article

* Google Scholar

17. 17. Felsenstein J. Evolutionary trees from DNA sequences: A maximum likelihood approach. J Mol Evol. 1 nov 1981;17(6):368‑76. pmid:7288891

* View Article

* PubMed/NCBI

* Google Scholar

18. 18. Rosemary A, Chika O, Jonathan O, Godwin I, Georgina O, Azuka O, et al. Genotyping performance evaluation of commercially available HIV-1 drug resistance test. PLOS ONE. 28 juin 2018;13(6):e0198246. pmid:29953436

* View Article

* PubMed/NCBI

* Google Scholar

19. 19. Thiam M, Diop-Ndiaye H, Kebe K, Vidal N, Diakhate-Lô R, Diouara AAM, et al. Performance of the ViroSeq HIV-1 genotyping system v2.0 on HIV-1 strains circulating in Senegal. Journal of Virological Methods. 1 mars 2013;188(1):97‑103. pmid:23266258

* View Article

* PubMed/NCBI

* Google Scholar

20. 20. Aghokeng AF, Mpoudi-Ngole E, Chia JE, Edoul EM, Delaporte E, Peeters M. High Failure Rate of the ViroSeq HIV-1 Genotyping System for Drug Resistance Testing in Cameroon, a Country with Broad HIV-1 Genetic Diversity. Journal of Clinical Microbiology. 21 déc 2020;49(4):1635‑41.

* View Article

* Google Scholar

21. 21. Kebe K, Thiam M, Diagne Gueye NR, Diop H, Dia A, Signate Sy H, et al. High Rate Of Antiretroviral Drug Resistance Mutations in HIV Type 1-Infected Senegalese Children in Virological Failure on First-Line Treatment According to the World Health Organization Guidelines. AIDS Research and Human Retroviruses. févr 2013;29(2):242‑9. pmid:22860571

* View Article

* PubMed/NCBI

* Google Scholar

22. 22. Tadesse BT, Kinloch NN, Baraki B, Lapointe HR, Cobarrubias KD, Brockman MA, et al. High Levels of Dual-Class Drug Resistance in HIV-Infected Children Failing First-Line Antiretroviral Therapy in Southern Ethiopia. Viruses. févr 2018;10(2):60. pmid:29389912

* View Article

* PubMed/NCBI

* Google Scholar

23. 23. Khamadi SA, Bahemana E, Dear N, Mavere C, George F, Kapene R, et al. Factors Associated With Viral Suppression and Drug Resistance in Children and Adolescents Living With HIV in Care and Treatment Programs in Southern Tanzania. J Pediatric Infect Dis Soc. 30 juin 2023;12(6):353‑63. pmid:37279560

* View Article

* PubMed/NCBI

* Google Scholar

24. 24. Mutwa PR, Boer KR, Rusine J, Muganga N, Tuyishimire D, Schuurman R, et al. Long-term effectiveness of combination antiretroviral therapy and prevalence of HIV drug resistance in HIV-1-infected children and adolescents in Rwanda. Pediatr Infect Dis J. janv 2014;33(1):63‑9. pmid:24352189

* View Article

* PubMed/NCBI

* Google Scholar

25. 25. Louis FJ, Segaren N, Desinor O, Beard RS, Jean-Louis R, Chang J, et al. High levels of HIV-1 drug resistance in children who acquired HIV infection through mother to child transmission in the era of Option B+, Haiti, 2013–2014. The Pediatric infectious disease journal. mai 2019;38(5):503.

* View Article

* Google Scholar

26. 26. Muri L, Gamell A, Ntamatungiro AJ, Glass TR, Luwanda LB, Battegay M, et al. Development of HIV drug resistance and therapeutic failure in children and adolescents in rural Tanzania: an emerging public health concern. AIDS (London, England). 1 janv 2017;31(1):61. pmid:27677163

* View Article

* PubMed/NCBI

* Google Scholar

27. 27. Yan L, Yu F, Liang J, Cheng Y, Li H, Zhao Q, et al. Drug resistance profiles and influencing factors among HIV-infected children and adolescents receiving long-term ART: a multicentre observational study in China. J Antimicrob Chemother. 23 févr 2022;77(3):727‑34. pmid:35195695

* View Article

* PubMed/NCBI

* Google Scholar

28. 28. Campbell TB, Shulman NS, Johnson SC, Zolopa AR, Young RK, Bushman L, et al. Antiviral Activity of Lamivudine in Salvage Therapy for Multidrug-Resistant HIV-1 Infection. Clinical Infectious Diseases. 15 juill 2005;41(2):236‑42. pmid:15983922

* View Article

* PubMed/NCBI

* Google Scholar

29. 29. Eron JJ, Benoit SL, Jemsek J, MacArthur RD, Santana J, Quinn JB, et al. Treatment with Lamivudine, Zidovudine, or Both in HIV-Positive Patients with 200 to 500 CD4+ Cells per Cubic Millimeter. New England Journal of Medicine. 21 déc 1995;333(25):1662‑9.

* View Article

* Google Scholar

30. 30. Penda CI, Mbonjo MM, Fokam J, Djeuda ABD, Grace N, Ndongo FA, et al. Rate of virological failure and HIV-1 drug resistance among HIV-infected adolescents in routine follow-up on health facilities in Cameroon. PLOS ONE. 26 oct 2022;17(10):e0276730. pmid:36288365

* View Article

* PubMed/NCBI

* Google Scholar

31. 31. Larder BA, Kemp SD. Multiple Mutations in HIV-1 Reverse Transcriptase Confer High-Level Resistance to Zidovudine (AZT). Science. déc 1989;246(4934):1155‑8. pmid:2479983

* View Article

* PubMed/NCBI

* Google Scholar

32. 32. Averbuch D, Schapiro JM, Lanier ER, Gradstein S, Gottesman G, Kedem E, et al. Diminished selection for thymidine-analog mutations associated with the presence of M184V in Ethiopian children infected with HIV subtype C receiving lamivudine-containing therapy. Pediatr Infect Dis J. nov 2006;25(11):1049‑56. pmid:17072129

* View Article

* PubMed/NCBI

* Google Scholar

33. 33. Boyer PL, Currens, McMahon JB, Boyd MR, Hughes SH. Analysis of nonnucleoside drug-resistant variants of human immunodeficiency virus type 1 reverse transcriptase. Journal of Virology. avr 1993;67(4):2412‑20.

* View Article

* Google Scholar

34. 34. Hsiou Y, Ding J, Das K, Clark AD, Boyer PL, Lewi P, et al. The Lys103Asn mutation of HIV-1 RT: a novel mechanism of drug resistance11Edited by J. Karn. Journal of Molecular Biology. 1 juin 2001;309(2):437‑45.

* View Article

* Google Scholar

35. 35. Tagnouokam-Ngoupo PA, Penda IC, Mbougua JBT, Ndiang ST, Septoh FY, Kenne A, et al. Virological failure and antiretroviral resistance among HIV-infected children after five years follow-up in the ANRS 12225-PEDIACAM cohort in Cameroon. PLOS ONE. 18 mars 2021;16(3):e0248642. pmid:33735301

* View Article

* PubMed/NCBI

* Google Scholar

36. 36. Rubio-Garrido M, Reina G, Ndarabu A, Rodriguez-Galet A, Valadés-Alcaraz A, Barquín D, et al. High drug resistance levels could compromise the control of HIV infection in paediatric and adolescent population in Kinshasa, the Democratic Republic of Congo. PLOS ONE. 15 avr 2021;16(4):e0248835.

* View Article

* Google Scholar

37. 37. Tchiakpe E, Keke RK, Vidal N, Ahoussinou C, Sekpe O, Dagba HG, et al. Moderate rate of transmitted resistance mutations to antiretrovirals and genetic diversity in newly HIV-1 patients diagnosed in Benin. BMC Res Notes. déc 2020;13(1):1‑8. pmid:32616057

* View Article

* PubMed/NCBI

* Google Scholar

38. 38. Montavon C, Toure-Kane C, Liegeois F, Mpoudi E, Bourgeois A, Vergne L, et al. Most env and gag Subtype A HIV-1 Viruses Circulating in West and West Central Africa Are Similar to the Prototype AG Recombinant Virus IBNG: JAIDS Journal of Acquired Immune Deficiency Syndromes. avr 2000;23(5):363‑74.

* View Article

* Google Scholar

39. 39. Ho DD, Neumann AU, Perelson AS, Chen W, Leonard JM, Markowitz M. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature. janv 1995;373(6510):123‑6. pmid:7816094

* View Article

* PubMed/NCBI

* Google Scholar

40. 40. Hemelaar J, Elangovan R, Yun J, Dickson-Tetteh L, Fleminger I, Kirtley S, et al. Global and regional molecular epidemiology of HIV-1, 1990–2015: a systematic review, global survey, and trend analysis. The Lancet Infectious Diseases. 1 févr 2019;19(2):143‑55. pmid:30509777

* View Article

* PubMed/NCBI

* Google Scholar

41. 41. E, Baldrich-Rubio, Anagonou S, Stirrups K, Lafia E, Candotti D, Lee H, et al. A complex human immunodeficiency virus type 1 A/G/J recombinant virus isolated from a seronegative patient with AIDS from Benin, West Africa. Journal of General Virology. 1 mai 2001;82(5):1095‑106.

42. 42. Nazziwa J, Faria NR, Chaplin B, Rawizza H, Kanki P, Dakum P, et al. Characterisation of HIV-1 Molecular Epidemiology in Nigeria: Origin, Diversity, Demography and Geographic Spread. Sci Rep. 26 févr 2020;10(1):3468. pmid:32103028

* View Article

* PubMed/NCBI

* Google Scholar

43. 43. Meloni ST, Kim B, Sankalé JL, Hamel DJ, Tovanabutra S, Mboup S, et al. Distinct Human Immunodeficiency Virus Type 1 Subtype A Virus Circulating in West Africa: Sub-Subtype A3. Journal of Virology. 15 nov 2004;78(22):12438‑45. pmid:15507630

* View Article

* PubMed/NCBI

* Google Scholar

44. 44. Palm AA, Esbjörnsson J, Månsson F, Kvist A, Isberg PE, Biague A, et al. Faster Progression to AIDS and AIDS-Related Death Among Seroincident Individuals Infected With Recombinant HIV-1 A3/CRF02_AG Compared With Sub-subtype A3. The Journal of Infectious Diseases. 1 mars 2014;209(5):721‑8. pmid:23935204

* View Article

* PubMed/NCBI

* Google Scholar

45. 45. Meloni ST, Sankalé JL, Hamel DJ, Eisen G, Guéye-Ndiaye A, Mboup S, et al. Molecular Epidemiology of Human Immunodeficiency Virus Type 1 Sub-Subtype A3 in Senegal from 1988 to 2001. Journal of Virology. 15 nov 2004;78(22):12455‑61. pmid:15507632

* View Article

* PubMed/NCBI

* Google Scholar

46. 46. Heyndric X L., Janssens W., Alary M., Fransen K., Vereecken K., Coppens S., et al. Note de séquence: Variabilité génétique du VIH de type 1 au Bénin [Internet]. 1996 [cité 13 nov 2024]. Disponible sur: https://login.research4life.org/tacsgr1www_liebertpub_com/doi/epdf/10.1089/aid.1996.12.1495

* View Article

* Google Scholar

Citation: Dagba Gbessin EH, Tchiakpe E, Keke RK, Vidal N, Gomgnimbou MK, Sina H, et al. (2025) HIV-1 resistance mutations and genetic diversity among children failing antiretroviral treatment in five healthcare facilities in Benin, West Africa. PLoS ONE 20(1): e0317882. https://doi.org/10.1371/journal.pone.0317882

About the Authors:

Edwige Hermione Dagba Gbessin

Roles: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

E-mail: [email protected]

Affiliations: NAZI BONI University, Bobo-Dioulasso, Burkina Faso, National Reference Laboratory of Health Program Fighting Against AIDS in Benin (LNR/PSLS), Health Ministry, Akpakpa, Littoral, Benin

ORICD: https://orcid.org/0009-0005-6950-1668

Edmond Tchiakpe

Roles: Formal analysis, Validation, Writing – review & editing

Affiliations: National Reference Laboratory of Health Program Fighting Against AIDS in Benin (LNR/PSLS), Health Ministry, Akpakpa, Littoral, Benin, Faculty of Sciences and Technology (FAST) and Institute of Applied Biomedical Sciences (ISBA), Department of Biochemistry and Cellular Biology, Laboratory of Cell Biology and Physiology, University of Abomey-Calavi, Abomey-Calavi, Atlantic, Benin

René Kpemahouton Keke

Roles: Conceptualization, Project administration, Resources, Validation

Affiliation: National Reference Laboratory of Health Program Fighting Against AIDS in Benin (LNR/PSLS), Health Ministry, Akpakpa, Littoral, Benin

Nicole Vidal

Roles: Software, Validation

Affiliation: UMI233 -TransVIHMI, Université de Montpellier, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Recherche pour le Développement (IRD), Montpellier, France

Michel Kiréopori Gomgnimbou