Current and historic HIV-1 molecular epidemiology in paediatric and adult population from Kinshasa in the Democratic Republic of Congo

Transmitted Drug Resistance and HIV Diversity Among Adolescents Newly Diagnosed With HIV in Spain

BACKGROUND

Virologic characterization of newly HIV-diagnosed adolescents could help to improve their specific needs. The objective was to describe the transmitted drug resistance mutations (TDR) and its transmission by clusters in this population in Spain.

METHODS

TDR to retrotranscriptase and protease inhibitors included in the WHO TDR list 2009 implemented in the Calibrated Population Resistance tool v8.0 (Stanford) were studied in HIV pol sequences from all HIV-diagnosed adolescents (12-19-year-old) enrolled during 2004-2019 period in the Spanish pediatric and adult (CoRISpe-CoRIS) cohorts. The found TDR were compared with the provided by the Stanford algorithm v9.0 2021. HIV-1 variants and transmission clusters were also studied.

RESULTS

Among 410 HIV-1 adolescents diagnosed, 141 (34.4%) had available ART-naive sequences. They were mostly male (81.6%), Spanish (55.3%) and with behavioral risk (92.2%), mainly male-to-male sexual contact (63.1%). TDR prevalence was significantly higher by Stanford versus WHO list (18.4% vs. 7.1%; P = 0.004). The most prevalent TDR by the WHO list was K103N (3.6%) and by Stanford E138A (6.6%), both at retrotranscriptase. E138A, related to rilpivirine/etravirine resistance, was absent in the WHO list. One in 4 adolescents carried HIV-1 non-B variants. We described 5 transmission clusters, and 2 carried TDR mutations.

CONCLUSIONS

Our data suggest a high TDR prevalence in adolescents with a new HIV diagnosis in Spain, similar to adults, 2 active TDR transmission clusters, and the need for the WHO TDR list update. These findings could have implications for the options of the recently available rilpivirine-related long-acting treatment and in first-line regimen election.

High Drug Resistance Levels Compromise the Control of HIV Infection in Pediatric and Adult Populations in Bata, Equatorial Guinea

A lack of HIV viral load (VL) and HIV drug resistance (HIVDR) monitoring in sub-Saharan Africa has led to an uncontrolled circulation of HIV-strains with drug resistance mutations (DRM), compromising antiretroviral therapy (ART). This study updates HIVDR data and HIV-1 variants in Equatorial Guinea (EG), providing the first data on children/adolescents in the country. From 2019−2020, 269 dried blood samples (DBS) were collected in Bata Regional Hospital (EG) from 187 adults (73 ART-naïve/114 ART-treated) and 82 children/adolescents (25 HIV-exposed-ART-naïve/57 ART-treated). HIV-1 infection was confirmed in Madrid by molecular/serological confirmatory tests and ART-failure by VL quantification. HIV-1 pol region was identified as transmitted/acquired DRM, predicted antiretroviral susceptibility (Stanfordv9.0) and HIV-1 variants (phylogeny). HIV infection was confirmed in 88.1% of the individuals and virological failure (VL > 1000 HIV-1-RNA copies/mL) in 84.2/88.9/61.9% of 169 ART-treated children/adolescents/adults. Among the 167 subjects with available data, 24.6% suffered a diagnostic delay. All 125 treated had experienced nucleoside retrotranscriptase inhibitors (NRTI); 95.2% were non-NRTI (NNRTI); 22.4% had experienced integrase inhibitors (INSTI); and 16% had experienced protease inhibitors (PI). At sampling, they had received 1 (37.6%), 2 (32%), 3 (24.8%) or 4 (5.6%) different ART-regimens. Among the 43 treated children−adolescents/37 adults with sequence, 62.8/64.9% carried viruses with major-DRM. Most harbored DRM to NNRTI (68.4/66.7%), NRTI (55.3/43.3%) or NRTI+NNRTI (50/33.3%). One adult and one child carried major-DRM to PI and none carried major-DRM to INSTI. Most participants were susceptible to INI and PI. DRM was absent in 36.2% of treated patients with VL > 1000 cp/mL, suggesting adherence failure. TDR prevalence in 59 ART-naïve adults was high (20.3%). One-half (53.9%) of the 141 subjects with pol sequence carried CRF02_AG. The observed high rate of ART-failure and transmitted/acquired HIVDR could compromise the 95-95-95-UNAIDS targets in EG. Routine VL and resistance monitoring implementation are mandatory for early detection of ART-failure and optimal rescue therapy selection ART regimens based on PI, and INSTI can improve HIV control in EG.

Drug resistance in children and adolescents with HIV in Panama

OBJECTIVES

The inadequacy of resistance monitoring in Latin America leads to circulation of HIV strains with drug resistance mutations (DRMs), compromising ART effectiveness. This study describes the DRM prevalence in HIV-infected paediatric patients in Panama.

METHODS

During 2018-19, plasma was collected from 76 HIV-infected children/adolescents (5 ART-naive, 71 treated) in Panama for HIV-1 DRM pol analysis, predicted antiretroviral (ARV) susceptibility by Stanford, and HIV-1 variant phylogenetic characterization.

RESULTS

HIV-1 pol sequences were recovered from 67 (88.2%) of 76 children/adolescents (median age 12 years), carrying 65 subtype B, 1 subtype G and 1 unique recombinant URF_A1B. Five were ART-naive and 62 ART-treated under virological failure (viraemia >50 copies/mL) with previous exposure to NRTIs, (100%), NNRTIs (45.2%), PIs (95.2%) and integrase strand transfer inhibitors (INSTIs, 17.7%). Among the treated patients, 34 (54.8%) carried resistant strains, with major DRMs to one (40.3%), two (9.7%) or three (4.8%) ARV families. Most of them harboured DRMs to NRTIs (58.5%) or NNRTIs (39%), but also major DRMs to PIs (4.9%) and INSTIs (6.5%). We also found dual-class NRTI + NNRTI (12.2%) and NNRTI + PI (2.6%) resistance. Two naive subjects carried viruses with DRMs to NRTIs and NRTI + NNRTI, respectively. Sequenced viruses presented high/intermediate resistance mainly to emtricitabine/lamivudine (48.9% each) and efavirenz/nevirapine (33.3% each). Most participants were susceptible to PIs (91.3%) and INSTIs (88.1%).

CONCLUSIONS

The high DRM prevalence to NRTIs and NNRTIs observed among treated HIV-infected children/adolescents in Panama justifies the need for routine resistance monitoring for optimal rescue therapy selection in this vulnerable population.

Immune surveillance for six vaccinable pathogens using paired plasma and dried blood spots in HIV infected and uninfected children in Kinshasa

Child vaccination reduces infant mortality rates. HIV-infected children present higher risk of diseases than non-infected. We report the protection coverage rates for 6 vaccine-preventable diseases in a paediatric population from the Democratic Republic of the Congo (DRC) and the impact of HIV infection, providing the first data on the validity of dried blood samples (DBS) to monitor the immune protection. During 2016–2018 DBS from 143 children/adolescents were collected in Kinshasa (DRC), being 52 HIV-infected. Forty-two had a paired plasma sample. Protective IgG was quantified (VirClia-IgG,VIRCELL) to obtain the optimal cut-off in IgG detection in DBS. ROC curves were generated with R software and statistical analyses with Stata. Protective IgG levels varied across pathogens, not reaching herd immunity. HIV-infected presented lower vaccine protection than uninfected for all analyzed pathogens, except rubella, with statistically significant differences for measles (30.8% vs. 53.8%; p = 0.008) and tetanus (3.8% vs. 22%; p = 0.0034). New cut-offs were calculated when using DBS to improve test performance. We reinforce the necessity to increase pediatric vaccination coverage in Kinshasa, especially in HIV seropositive, with less capacity to maintain adequate antibody levels. DBS were useful to monitor vaccination coverage in seroprevalence studies in resource-limited settings, after optimizing the cut-off value for each pathogen.

Revisiting the recombinant history of HIV-1 group M with dynamic network community detection

Recombination is a major mechanism through which HIV type 1 (HIV-1) maintains genetic diversity and interferes with viral eradication efforts. There is growing evidence demonstrating a recombinant origin of primate lentiviruses including HIV-1 group M (HIV-1/M). Inferring the extent of recombination across the entire HIV-1/M genome is of great importance as it provides deeper insights into the origin, dynamics, and evolution of the global pandemic. Here we propose an alternative method that can reconstruct the extent of genome-wide recombination in HIV-1, uncover reticulate patterns, and serve as a framework for HIV-1 classification. Our method provides an alternative approach for understanding the roles of virus recombination in the early evolutionary history of zoonosis for other emerging viruses.

The prevailing abundance of full-length HIV type 1 (HIV-1) genome sequences provides an opportunity to revisit the standard model of HIV-1 group M (HIV-1/M) diversity that clusters genomes into largely nonrecombinant subtypes, which is not consistent with recent evidence of deep recombinant histories for simian immunodeficiency virus (SIV) and other HIV-1 groups. Here we develop an unsupervised nonparametric clustering approach, which does not rely on predefined nonrecombinant genomes, by adapting a community detection method developed for dynamic social network analysis. We show that this method (dynamic stochastic block model [DSBM]) attains a significantly lower mean error rate in detecting recombinant breakpoints in simulated data (quasibinomial generalized linear model (GLM), P<8×10−8), compared to other reference-free recombination detection programs (genetic algorithm for recombination detection [GARD], recombination detection program 4 [RDP4], and RDP5). When this method was applied to a representative sample of n = 525 actual HIV-1 genomes, we determined k = 29 as the optimal number of DSBM clusters and used change-point detection to estimate that at least 95% of these genomes are recombinant. Further, we identified both known and undocumented recombination hotspots in the HIV-1 genome and evidence of intersubtype recombination in HIV-1 subtype reference genomes. We propose that clusters generated by DSBM can provide an informative framework for HIV-1 classification.

HIV-1 diagnosis using dried blood spots from patients in Kinshasa, DRC: a tool to detect misdiagnosis and achieve World Health Organization 2030 targets

INTRODUCTION

Currently, only 54% of the population of the Democratic Republic of the Congo (DRC) know their HIV status. The aim of this study was to detect HIV misdiagnosis from rapid diagnostic tests (RDT) and to evaluate serological immunoassays using dried blood spots (DBS) from patients in Kinshasa, DRC.

METHODS

Between 2016 and 2018, 365 DBS samples were collected from 363 individuals and shipped to Spain. The samples were from people with a new HIV positive (n = 123) or indeterminate (n = 23) result, known HIV-positive patients (n = 157), and a negative control group (n = 62). HIV serology was performed using Elecsys HIV combi PT (Roche), VIDAS HIV Duo Quick (BioMérieux), and Geenius (Bio-Rad). In addition, HIV RNA detection was performed in all samples using the COBAS AmpliPrep/COBAS Taqman HIV-1 Test 2.0 (Roche).

RESULTS

Overall, 272 samples were found to be positive and 93 to be negative for HIV serology. The sensitivity was 100% for both Elecsys and VIDAS techniques, but specificity was slightly higher for the VIDAS test: 100% (96.1-100%) vs 98.9% (94.1-99.9%). Of the 23 indeterminate cases using RDT, only three cases were true-positives with a detectable viral load. Eleven samples out of the 280 classified as positive by RDT corresponded to nine patients who had received a false diagnosis of HIV through RDT (3.9%); six of them had been on antiretroviral therapy for at least 2 years.

CONCLUSIONS

Elecsys HIV combi PT and VIDAS HIV Duo Quick immunoassays showed high sensitivity and specificity when using DBS. RDT-based serological diagnosis can lead to HIV misdiagnosis with personal and social consequences in sub-Saharan Africa.

The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review

To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.

Viral reverse engineering using Artificial Intelligence and big data COVID-19 infection with Long Short-term Memory (LSTM)

This research presents a reverse engineering approach to discover the patterns and evolution behavior of SARS-CoV-2 using AI and big data. Accordingly, we have studied five viral families (Orthomyxoviridae, Retroviridae, Filoviridae, Flaviviridae, and Coronaviridae) that happened in the era of the past one hundred years. To capture the similarities, common characteristics, and evolution behavior for prediction concerning SARS-CoV-2. And how reverse engineering using Artificial intelligence (AI) and big data is efficient and provides wide horizons. The results show that SARS-CoV-2 shares the same highest active amino acids (S, L, and T) with the mentioned viral families. As known, that affects the building function of the proteins. We have also devised a mathematical formula representing how we calculate the evolution difference percentage between each virus concerning its phylogenic tree. It shows that SARS-CoV-2 has fast mutation evolution concerning its time of arising. Artificial Intelligence (AI) is used to predict the next evolved instance of SARS-CoV-2 by utilizing the phylogenic tree data as a corpus using Long Short-term Memory (LSTM). This paper has shown the evolved viral instance prediction process on ORF7a protein from SARS-CoV-2 as the first stage to predict the complete mutant virus. Finally, in this research, we have focused on analyzing the virus to its primary factors by reverse engineering using AI and big data to understand the viral similarities, patterns, and evolution behavior to predict future viral mutations of the virus artificially in a systematic and logical way.

High drug resistance levels could compromise the control of HIV infection in paediatric and adolescent population in Kinshasa, the Democratic Republic of Congo

Background

The inadequacy of HIV viraemia and resistance monitoring in Africa leads to uncontrolled circulation of HIV strains with drug resistance mutations (DRM), compromising antiretroviral therapy (ART) effectiveness. This study describes the DRM prevalence and its therapeutic impact in HIV-infected pediatric patients from Kinshasa (Democratic Republic of Congo, DRC).

Methods

From 2016–2018, dried blood were collected from 71 HIV-infected children and adolescents under ART in two hospitals in Kinshasa for HIV-1 DRM pol analysis, predicted ARV-susceptibility by Stanford and phylogenetic characterization.

Results

HIV-1 sequences were recovered from 55 children/adolescents with 14 years of median-age. All had received nucleoside and non-nucleoside reverse transcriptase inhibitors (NRTI, NNRTI), 9.1% protease inhibitors (PI) and only one integrase inhibitor (INI). Despite the use of ART, 89.1% showed virological failure and 67.3% carried viruses with major-DRM to one (12.7%), two (47.3%), or three (5.5%) ARV-families. Most children/adolescents harbored DRM to NNRTI (73.5%) or NRTI (61.2%). Major-DRM to PI was present in 8.3% and minor-DRM to INI in 15%. Dual-class-NRTI+NNRTI resistance appeared in 53.1% of patients. Viruses presented high/intermediate resistance to nevirapine (72.9% patients), efavirenz (70.9%), emtricitabine/lamivudine (47.9%), rilpivirine (41.7%), etravirine (39.6%), doravidine (33.3%), zidovudine (22.9%), among others. Most participants were susceptible to INI and PI. Great diversity of variants was found, with a high rate (40%) of unique recombinants.

Conclusion

The high DRM prevalence observed among HIV-infected children and adolescents in Kinshasa could compromise the 95-95-95-UNAIDS targets in the DRC. It also reinforces the need for routine resistance monitoring for optimal rescue therapy election in this vulnerable population to control the spread of resistant HIV in the country.