Abstract

BackgroundAntiretroviral therapy (ART) has improved the survival of HIV infected persons. However, rapid scale-up of ART and the high HIV-1 genetic variability, has greatly influenced the emergence of drug-resistant strains. This constitutes a potential threat to achieving the UNAIDS’ 90-90-90 goals by 2020. We investigated the prevalent HIV-1 genotypes, drug resistance-associated mutations and assessed some predictors of the occurrence of these mutations.MethodsThis was a hospital-based cross-sectional study conducted between October 2010 and June 2012. Participants were consecutively enrolled from selected HIV treatment centers of the Southwest and Northwest regions of Cameroon. Viral load was determined with the automated Abbott Real-time HIV-1 m2000rt System. HIV genotyping and antiretroviral resistance mutations analysis were performed using Bayer’s HIV-1 TRUGENE™ Genotyping Kit and OpenGene DNA Sequencing system. The drug resistance mutation was interpreted with the Stanford HIV database. Epidemiological data were obtained using pre-tested semi-structured questionnaires.ResultsOf the 387 participants, 239 were successfully genotyped. The median age of these participants was 33 years (interquartile range, IQR: 28–40 years), and a majority (65.7%) were female. A total of 29.3% of the participants were receiving ART. The median duration of ART was 10.5 months (IQR: 4–17.25 months). The median CD4 count and log10 viral load of study participants were 353.5 cells/ml (IQR:145–471) and 4.89 copies/ml (IQR: 3.91–5.55) respectively. CRF02 (A/G) (69%) was the most prevalent subtype followed by G (8.2%) and F (6.7%). Overall, resistance mutations were present in 37.1% of ART-experienced and 10.7% of ART-naive patients. Nucleoside reverse transcriptase inhibitors (NRTI) mutations occurred in 30% of ART-experienced and 2.4% of ART-naïve patients, while non-nucleoside reverse transcriptase inhibitors (NNRTI) mutations occurred in 34.2% of ART-experienced and 10.1% of -naïve patients. M184V (8.4%, 20/239) and K103N (5.4%, 13/239) were the most prevalent mutations. Major protease inhibitor mutations occurred in 3 (1.3%) out of the 239 sequences. The duration of ART independently predicted the occurrence of resistance mutation among ART-experienced patients.ConclusionThe high resistance to NNRTIs, which are the main support to the backbone (NRTIs) first-line antiretroviral regimen in Cameroon, has prompted the need to rollout an integrase strand transfer inhibitor regimen (containing Dolutegravir) with a higher genetic barrier to resistance as the preferred first line regimen.

Highlights

  • Preventable, HIV infection continues to be a major global public health concern

  • The high resistance to nonnucleoside reverse transcriptase inhibitors (NNRTI), which are the main support to the backbone (NRTIs) firstline antiretroviral regimen in Cameroon, has prompted the need to rollout an integrase strand transfer inhibitor regimen with a higher genetic barrier to resistance as the preferred first line regimen

  • It became evident from phylogenetic analysis that some isolates combined with different subtypes in different regions of their genomes to give rise to mosaic HIV-1 genomes referred to as circulating recombinant forms (CRF) [8]

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Summary

Introduction

HIV infection continues to be a major global public health concern. HIV genetic diversity is one of its most significant features that may directly influence the global distribution, vaccine design, therapy success rate, disease progression, transmissibility [2] and the emergence of drug-resistant strains [3]. West and Central African countries have a wide distribution of HIV-1 M subtypes and Cameroon probably harbours the highest number of HIV-1 subtypes [10]. Rapid scale-up of ART and the high HIV-1 genetic variability, has greatly influenced the emergence of drug-resistant strains. This constitutes a potential threat to achieving the UNAIDS’ 90-90-90 goals by 2020. We investigated the prevalent HIV-1 genotypes, drug resistance-associated mutations and assessed some predictors of the occurrence of these mutations

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