Antiretroviral (ARV) Therapy in Resource Poor Countries: What do we Need in Real Life?

Significant progresses have been made in the last 5 years towards the ultimate goal to provide universal access to care for all HIV/AIDS patients needing antiretroviral treatment in resource-poor countries. However, many barriers are still to be overcome, including (●) cost of care for the individual, (●) stigma, (●) lack of qualified human resources and infrastructure, especially in the rural setting, (●) rescue drugs for failing patients and (●) pediatric formulations. Priority actions to be promoted if the fight against HIV/AIDS is to be successful include: (i) promoting access to care in the rural areas, (ii) strengthening of basic health infrastructures, (iii) waiving of users’ fee to get ARV, (iv) a larger variety of drugs, with particular regard to fixed dose combination third line drugs and pediatric formulations, (v) local quality training and (vi) high quality basic and translational research. While the universal access to HIV care is crucial in developing countries, a strong emphasis on prevention should be maintained along

Fitness Ranking of Individual Mutants Drives Patterns of Epistatic Interactions in HIV-1

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Comparative determination of HIV-1 co-receptor tropism by Enhanced Sensitivity Trofile, gp120 V3-loop RNA and DNA genotyping

BACKGROUND: Trofile is the prospectively validated HIV-1 tropism assay. Its use is limited by high costs, long turn-around time, and inability to test patients with very low or undetectable viremia. We aimed at assessing the efficiency of population genotypic assays based on gp120 V3-loop sequencing for the determination of tropism in plasma viral RNA and in whole-blood viral DNA. Contemporary and follow-up plasma and whole-blood samples from patients undergoing tropism testing via the enhanced sensitivity Trofile (ESTA) were collected. Clinical and clonal geno2pheno[coreceptor] (G2P) models at 10% and at optimised 5.7% false positive rate cutoff were evaluated using viral DNA and RNA samples, compared against each other and ESTA, using Cohen's kappa, phylogenetic analysis, and area under the receiver operating characteristic (AUROC). RESULTS: Both clinical and clonal G2P (with different false positive rates) showed good performances in predicting the ESTA outcome (for V3 RNA-based clinical G2P at 10% false positive rate AUROC = 0.83, sensitivity = 90%, specificity = 75%). The rate of agreement between DNA- and RNA-based clinical G2P was fair (kappa = 0.74, p < 0.0001), and DNA-based clinical G2P accurately predicted the plasma ESTA (AUROC = 0.86). Significant differences in the viral populations were detected when comparing inter/intra patient diversity of viral DNA with RNA sequences. CONCLUSIONS: Plasma HIV RNA or whole-blood HIV DNA V3-loop sequencing interpreted with clinical G2P is cheap and can be a good surrogate for ESTA. Although there may be differences among viral RNA and DNA populations in the same host, DNA-based G2P may be used as an indication of viral tropism in patients with undetectable plasma viremia

Standing genetic variation and the evolution of drug resistance in HIV

Drug resistance remains a major problem for the treatment of HIV. Resistance can occur due to mutations that were present before treatment starts or due to mutations that occur during treatment. The relative importance of these two sources is unknown. We study three different situations in which HIV drug resistance may evolve: starting triple-drug therapy, treatment with a single dose of nevirapine and interruption of treatment. For each of these three cases good data are available from literature, which allows us to estimate the probability that resistance evolves from standing genetic variation. Depending on the treatment we find probabilities of the evolution of drug resistance due to standing genetic variation between 0 and 39%. For patients who start triple-drug combination therapy, we find that drug resistance evolves from standing genetic variation in approximately 6% of the patients. We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters. We find that both, the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-parameters that determine the probability that resistance evolves from standing genetic variation. Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.Comment: 33 pages 6 figure

The Emergence of HIV Transmitted Resistance in Botswana: “When Will the WHO Detection Threshold Be Exceeded?”

BACKGROUND: The Botswana antiretroviral program began in 2002 and currently treats 42,000 patients, with a goal of treating 85,000 by 2009. The World Health Organization (WHO) has begun to implement a surveillance system for detecting transmitted resistance that exceeds a threshold of 5%. However, the WHO has not determined when this threshold will be reached. Here we model the Botswana government's treatment plan and predict, to 2009, the likely stochastic evolution of transmitted resistance. METHODS: We developed a model of the stochastic evolution of drug-resistant strains and formulated a birth-death Master equation. We analyzed this equation to obtain an analytical solution of the probabilistic evolutionary trajectory for transmitted resistance, and used treatment and demographic data from Botswana. We determined the temporal dynamics of transmitted resistance as a function of: (i) the transmissibility (i.e., fitness) of the drug-resistant strains that may evolve and (ii) the rate of acquired resistance. RESULTS: Transmitted resistance in Botswana will be unlikely to exceed the WHO's threshold by 2009 even if the rate of acquired resistance is high and the strains that evolve are half as fit as the wild-type strains. However, we also found that transmission of drug-resistant strains in Botswana could increase to ∼15% by 2009 if the drug-resistant strains that evolve are as fit as the wild-type strains. CONCLUSIONS: Transmitted resistance will only be detected by the WHO (by 2009) if the strains that evolve are extremely fit and acquired resistance is high. Initially after a treatment program is begun a threshold lower than 5% should be used; and we advise that predictions should be made before setting a threshold. Our results indicate that it may be several years before the WHO's surveillance system is likely to detect transmitted resistance in other resource-poor countries that have significantly less ambitious treatment programs than Botswana

Impact of long-term viral suppression in CD4+ recovery of HIV-children on Highly Active Antiretroviral Therapy

BACKGROUND: The effects of HAART may differ between children and adults because children have a developing immune system, and the long-term immunological outcome in HIV-infected children on HAART is not well-known. A major aim of our study was to determine CD4+ evolution associated with long-term VL control during 4 years of observation on HAART. METHODS: We carried out a retrospective study on a cohort of 160 vertically HIV-infected children. It was carried out from 1996 to 2004 in six large Spanish pediatric referral hospitals. We compared 33 children who had long-term VL suppression (VL ≤400 copies/ml) in the first 12 months of follow-up and maintained that level throughout follow-up (Responders-group), and 127 children with persistently detectable VL in spite of ART switches (Non-Responders-group). RESULTS: We observed a quick initial and significant increase in CD4(+ )counts from the baseline to 12 months on HAART in both groups (p < 0.01). The Non-Responders group sustained CD4+ increases and most of these children maintained high CD4(+ )level counts (≥25%). The Non-Responders group reached a plateau between 26% and 27% CD4(+ )at the first 12 months of follow-up that remained stable during the following 3 years. However, the Responders group reached a plateau between 30% and 32% CD4(+ )at 24, 36 and 48 months of follow-up. We found that the Responders group had higher CD4(+ )count values and higher percentages of children with CD4(+ )≥25% than the Non-Responders group (p < 0.05) after month 12. CONCLUSION: Long-term VL suppression in turn induces large beneficial effects in immunological responses. However, it is not indispensable to recover CD4(+ )levels