11 research outputs found
HIV Drug Resistance Surveillance in Honduras after a Decade of Widespread Antiretroviral Therapy.
We assessed HIV drug resistance (DR) in individuals failing ART (acquired DR, ADR) and in ART-naïve individuals (pre-ART DR, PDR) in Honduras, after 10 years of widespread availability of ART.365 HIV-infected, ART-naïve, and 381 ART-experienced Honduran individuals were enrolled in 5 reference centres in Tegucigalpa, San Pedro Sula, La Ceiba, and Choluteca between April 2013 and April 2015. Plasma HIV protease-RT sequences were obtained. HIVDR was assessed using the WHO HIVDR mutation list and the Stanford algorithm. Recently infected (RI) individuals were identified using a multi-assay algorithm.PDR to any ARV drug was 11.5% (95% CI 8.4-15.2%). NNRTI PDR prevalence (8.2%) was higher than NRTI (2.2%) and PI (1.9%, p500 vs. <350 CD4+ T cells/μL. PDR in recently infected individuals was 13.6%, showing no significant difference with PDR in individuals with longstanding infection (10.7%). The most prevalent PDR mutations were M46IL (1.4%), T215 revertants (0.5%), and K103NS (5.5%). The overall ADR prevalence in individuals with <48 months on ART was 87.8% and for the ≥48 months on ART group 81.3%. ADR to three drug families increased in individuals with longer time on ART (p = 0.0343). M184V and K103N were the most frequent ADR mutations. PDR mutation frequency correlated with ADR mutation frequency for PI and NNRTI (p<0.01), but not for NRTI. Clusters of viruses were observed suggesting transmission of HIVDR both from ART-experienced to ART-naïve individuals and between ART-naïve individuals.The global PDR prevalence in Honduras remains at the intermediate level, after 10 years of widespread availability of ART. Evidence of ADR influencing the presence of PDR was observed by phylogenetic analyses and ADR/PDR mutation frequency correlations
Recommended from our members
Identification of major routes of HIV transmission throughout Mesoamerica.
BackgroundMigration and travel are major drivers of the spread of infectious diseases. Geographic proximity and a common language facilitate travel and migration in Mesoamerica, which in turn could affect the spread of HIV in the region.Methods6092 HIV-1 subtype B partial pol sequences sampled from unique antiretroviral treatment-naïve individuals from Mexico (40.7%), Guatemala (24.4%), Honduras (19%), Panama (8.2%), Nicaragua (5.5%), Belize (1.4%), and El Salvador (0.7%) between 2011 and 2016 were included. Phylogenetic and genetic network analyses were performed to infer putative relationships between HIV sequences. The demographic and geographic associations with clustering were analyzed and viral migration patterns were inferred using the Slatkin-Maddison approach on 100 iterations of random subsets of equal number of sequences per location.ResultsA total of 1685/6088 (27.7%) of sequences linked with at least one other sequence, forming 603 putative transmission clusters (range: 2-89 individuals). Clustering individuals were significantly more likely to be younger (median age 29 vs 33years, p<0.01) and men-who-have-sex-with-men (40.4% vs 30.3%, p<0.01). Of the 603 clusters, 30 (5%) included sequences from multiple countries with commonly observed linkages between Mexican and Honduran sequences. Eight of the 603 clusters included >10 individuals, including two comprised exclusively of Guatemalans (52 and 89 individuals). Phylogenetic and migration analyses suggested that the Central and Southern regions of Mexico along with Belize were major sources of HIV throughout the region (p<0.01) with genetic flow southward from Mexico to the other nations of Mesoamerica. We also found evidence of significant viral migration within Mexico.ConclusionInternational clusters were infrequent, suggesting moderate migration between HIV epidemics of the different Mesoamerican countries. Nevertheless, we observed important sources of transnational HIV spread in the region, including Southern and Central Mexico and Belize
Potential for immune-driven viral polymorphisms to compromise antiretroviral-based preexposure prophylaxis for prevention of HIV-1 infection
ObjectiveLong-acting rilpivirine is a candidate for preexposure prophylaxis (PrEP) for prevention of HIV-1 infection. However, rilpivirine resistance mutations at reverse transcriptase codon 138 (E138X) occur naturally in a minority of HIV-1-infected persons; in particular those expressing human leukocyte antigen (HLA)-B18 where reverse transcriptase-E138X arises as an immune escape mutation. We investigate the global prevalence, B18-linkage and replicative cost of reverse transcriptase-E138X and its regional implications for rilpivirine PrEP.MethodsWe analyzed linked reverse transcriptase-E138X/HLA data from 7772 antiretroviral-naive patients from 16 cohorts spanning five continents and five HIV-1 subtypes, alongside unlinked global reverse transcriptase-E138X and HLA frequencies from public databases. E138X-containing HIV-1 variants were assessed for in-vitro replication as a surrogate of mutation stability following transmission.ResultsReverse transcriptase-E138X variants, where the most common were rilpivirine resistance-associated mutations E138A/G/K, were significantly enriched in HLA-B18-positive individuals globally (P = 3.5 × 10) and in all HIV-1 subtypes except A. Reverse transcriptase-E138X and B18 frequencies correlated positively in 16 cohorts with linked HIV/HLA genotypes (Spearman's R = 0.75; P = 7.6 × 10) and in unlinked HIV/HLA data from 43 countries (Spearman's R = 0.34, P = 0.02). Notably, reverse transcriptase-E138X frequencies approached (or exceeded) 10% in key epidemic regions (e.g. sub-Saharan Africa, Southeastern Europe) where B18 is more common. This, along with the observation that reverse transcriptase-E138X variants do not confer in-vitro replicative costs, supports their persistence, and ongoing accumulation in circulation over time.ConclusionsResults illustrate the potential for a natural immune-driven HIV-1 polymorphism to compromise antiretroviral-based prevention, particularly in key epidemic regions. Regional reverse transcriptase-E138X surveillance should be undertaken before use of rilpivirine PrEP
Phylogenetic relations between HIV sequences from ART-naïve and ART-experienced Honduran individuals.
<p>A Maximum Likelihood tree including HIV PR-RT sequences from 365 ART-naïve and 381 ART-experienced patients was built, using the General Time Reversible + Γ + I model to estimate genetic distances, with a gamma parameter of 0.4389 estimated for the dataset and 1000 bootstrap repetitions to assess significance. Drug resistance mutation sites as well as positions with less than 95% site coverage were eliminated from the alignment, with a total of 1162 positions included in the final dataset. Branch lengths are measured in number of substitutions per site. All analyses were conducted in MEGA6. Sequences from ART-naïve individuals are shown in grey and sequences from ART-experienced individuals in blue. Sequences with pre-ART drug resistance (PDR) to protease inhibitors (PI, pink), nucleoside RT inhibitors (NRTIs, green), non-nucleoside RT Inhibitors (NNRTIs, red), and more than one ARV family (purple) are coloured. B and non-B reference sequences (shown in black) were obtained from the Los Alamos HIV Database. A-D Clusters of viruses with PDR and bootstrap support >75% are amplified. HIVDR mutations present in the viruses at the tips are shown. Empty triangle, heterosexual male; full-triangle, men who have sex with men; empty circle, female; ART, antiretroviral treatment; USM, Unidad de Salud Metropolitana (La Ceiba); HMCR, Hospital Mario Catarino Rivas (San Pedro Sula); INCP, Instituto Nacional Cardio Pulmonar (Tegucigalpa).</p
Frequency of pre-ART and acquired HIV drug resistance mutations in Honduras April 2013-April 2015.
<p><sup>a</sup> Frequency in individuals with pre-ART drug resistance (PDR; defined with the WHO list of mutations for HIV drug resistance surveillance) to the corresponding drug class (PI, n = 7; NRTI, n = 7; NNRTI, n = 30). Mutations that contribute with drug resistance penalty scores in the Stanford algorithm are shown. Only mutations found in the cohort are shown. Mutations considered for the analysis are as follows</p><p>NRTIs: M41L, A62V, K65R, D67T, D67H, D67N, D67G, D67E, T69A, T69D, T69ins, T69N, T69C, T69I, T69G, T69S, K70G, K70Q, K70N, K70R, K70E, L74I, L74V, V75L, V75I, V75A, V75T, V75S, V75M, F77L, Y115F, F116Y, V118I, Q151M, M184VI, L210W, T215Y, T215A, T215F, T215CDESIV, K219QEN, K219R.</p><p>NNRTIs: V90I, A98G, L100I, K101E, K101P, K103NS, V106A, V106M, V108I, E138KQ, E138GAR, V179AT, V179D, V179E, V179L, V179F, Y181IV, Y181C, Y188L, Y188H, Y188C, G190S, G190A, G190E, G190C, P225H, F227L, M230L, K238T, Y318F.</p><p>PIs: L10F, K20I, L23I, L24I, D30N, V32I, L33F, E35G, K43T, M46IL, I47A, I47V, G48VM, I50L, I50V, F53L, F53Y, I54VA, I54L, I54M, I54ST, Q58E, G73CSTA, T74S, L76V, V82A, V82F, V82T, V82S, V82M, V82C, V82L, N83D, I84VAC, I85V, N88D, N88S, L90M.</p><p>Frequency of pre-ART and acquired HIV drug resistance mutations in Honduras April 2013-April 2015.</p
PDR in a Honduran HIV-1-infected cohort, April 2013-April 2015 (n = 365).
<p><sup>a</sup> Pre-Antiretroviral Treatment Drug Resistance (PDR) estimated using the WHO HIV transmitted drug resistance surveillance mutation list.</p><p><sup>b</sup> PDR estimated with the Stanford algorithm (v7.0), with a threshold of ≥15 for at least one antiretroviral drug of the specified class. ARV, Antiretroviral; NNRTI, Non-Nucleoside Reverse Transcriptase Inhibitors; NRTI, Nucleoside Reverse Transcriptase Inhibitors; PI, Protease Inhibitors.</p><p>PDR in a Honduran HIV-1-infected cohort, April 2013-April 2015 (n = 365).</p
HIVDR mutation frequency in Honduras meta-analysis 2002–20015.
<p>HIVDR mutation frequency was compared using data from two previously published studies: Lloyd et al. (median sampling year 2002) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142604#pone.0142604.ref013" target="_blank">13</a>], and Murillo et al. (median sampling year 2006) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142604#pone.0142604.ref014" target="_blank">14</a>]; and the present study (median sampling year 2014). Only mutations present in any of the comparison groups are shown. Mutations considered for the analysis include only WHO TDR surveillance mutations. NRTI, Nucleoside RT Inhibitors; NNRTI, Non-nucleoside RT Inhibitors; PI, protease inhibitors. * p<0.05 Fisher’s exact test.</p
HIVDR mutation frequency comparison in individuals with recent and longstanding infection.
<p>Recently infected individuals were identified using a multi-assay algorithm as described in Methods. Only mutations present in any of the comparison groups are shown. Mutations considered for the analysis include WHO TDR surveillance mutations as well as mutations contributing with penalty scores in the Stanford algorithm. For a comprehensive list of mutations considered refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142604#pone.0142604.t004" target="_blank">Table 4</a>. NRTI, Nucleoside RT Inhibitors; NNRTI, Non-nucleoside RT Inhibitors; PI, protease inhibitors; * p<0.05 Fisher’s exact test.</p
Correlations between PDR and ADR mutation frequency in Honduras.
<p>Pearson correlation coefficients were calculated for PDR mutation frequency vs. ADR mutation frequency at <48 and ≥48 months on ART, for the whole study period, for all DR mutations together and dividing them into ARV families. Each point represents one mutation. Some of the most relevant DR mutations are shown. PDR, pre-antiretroviral treatment drug resistance; ADR, acquired drug resistance; NRTI, Nucleoside RT Inhibitors; NNRTI, Non-nucleoside RT Inhibitors; PI, protease inhibitors.</p