HIV-1 subtype diversity and immuno-virological outcomes among adolescents failing antiretroviral therapy in Cameroon: A cohort study

Abstract

Objective: We sought to evaluate the variability of HIV-1 and its effect on immuno-virological response among adolescents living with perinatally acquired HIV (APHI).

Methods: A cohort study was conducted from 2018-2020 among 311 APHI receiving antiretroviral therapy (ART) in Cameroon. Sequencing of protease and reverse transcriptase regions was performed for participants experiencing virological failure, VF, (Plasma viral load, PVL ≥ 1000 RNA copies/ml). HIV-1 subtypes were inferred by phylogeny; immuno-virological responses were monitored at 3-time points (T1-T3). Cox regression modeling was used to estimate adjusted hazard ratios (aHRs) of progression to: CD4 < 250, and PVL > 5log10, adjusted for acquired drug resistance, gender, ART line, adherence, and duration on treatment; p < 0.05 was considered statistically significant.

Results: Of the 141 participants in VF enrolled, the male-female ratio was 1:1; mean age was 15 (±3) years; and median [IQR] duration on ART was 51 [46-60] months. In all phases, 17 viral clades were found with a predominant CRF02_AG (58.2%, 59.4%, and 58.3%). From T1-T3 respectively, there was an increasing CD4 count (213 [154-313], 366 [309-469], and 438 [364-569] cells/mm3) and decline log10 PVL (5.23, 4.43, and 4.43), similar across subtypes. Among participants with CRF02_AG infection, duration of treatment was significantly associated with both rates of progression to CD4 < 250, and PVL > 5log10, aHR = 0.02 (0.001-0.52), and aHR = 0.05 (0.01-0.47) respectively. Moreover, four potential new HIV-1 recombinants were identified (CRF02_AG/02D, CRF02_AG/02A1F2, D/CRF02_AG, and AF2/CRF02_AG), indicating a wide viral diversity.

Conclusion: Among APHI in settings like Cameroon, there is a wide genetic diversity of HIV-1, driven by CRF02_AG and with potential novel clades due to ongoing recombination events. Duration of treatment significantly reduces the risk of disease progression.

Fig 1

a: Trends of HIVDR across time points. Blue line: the decreasing trend of HIVDR over time. Error bars denote standard error.b: Trends of HIV drug resistance with respect to antiretroviral drug classes. Error bars denote standard error.

Fig 2

a: Rich genetic diversity of HIV-1 subtypes and genetic variants in the study population. b: Median CD4 count rise over time across subtypes. Error bars denote standard error. c: Median log plasma viral load decreases over time. Error bars denote standard error.

Fig 3

a: Kaplan Meier analysis of time estimate to reach CD4 count < 250 cells/mm³. b: Probability of plasma viral load > 5 log RNA copies/mL over time. c: Maximum likelihood phylogenetic tree of the Protease-Reverse transcriptase gene regions of study participant sequences. This depicts broad genetic diversity with a wide inter/intra subtype recombination. d: Splits Tree analysis results: Maximum likelihood phylogenetic tree of the Protease-Reverse transcriptase gene regions of the four (CNPS029, CME125, HDMF009, and HDMB015) inter-subtype recombinants identified in the study.