Background: Resistance to antiretroviral drugs is a major challenge among Human Immunodeficiency Virus (HIV) positive patients receiving antiretroviral therapy (ART). Mutations that arise as a result of this are diverse across the various drugs, drug classes, drug regimens and subtypes. In Uganda, there is a paucity of information on how these mutations differ among the different drug regimens and the predominant HIV-1 subtypes. The purpose of this study was to determine mutation profile differences between first-line drug regimens: TDF/3TC/EFV and AZT/3TC/EFV and HIV-1 subtypes: A and D in Uganda. The study also investigated the potential usage of rilpivirine, doravirine and etravirine in patients who failed treatment on efavirenz. Methods: A retrospective study was conducted on 182 archived plasma samples obtained from patients who were experiencing virological failure between 2006 and 2017 at five Joint Clinical Research Center (JCRC) sites in Uganda. Sanger sequencing of the Reverse Transcriptase (RT) gene from codons 1-300 was done. Mutation scores were generated using the Stanford University HIV Drug Resistance Database. A Chi-square test was used to determine the association between drug resistance mutations (DRMs) and drug regimens or HIV-1 subtypes. Results: The prevalence of DRMs was 84.6% among patients failing a first-line efavirenz (EFV)-based regimen. The most prevalent Nucleoside Reverse Transcriptase Inhibitor (NRTI) mutations were M184V/I (67.3%), K219/Q/E (22.6%) and K65R (21.1%). While K103N (50.8%) and G190A/S/E/G (29.1%) were the most prevalent Non-Nucleoside Reverse Transcriptase Inhibitor (NNTRI) mutations. As expected, discriminatory DRMs such as K65R, L74I, and Y115F were noted in Tenofovir (TDF) containing regimens while the Thymidine Analogue Mutations (TAMs) L210W and T215 mutations were in Zidovudine (AZT)-based regimens. No significant difference (p = 0.336) was found for overall DRMs between HIV-1 subtypes A and D. Among the patients who had resistance to EFV, 37 (23.6%) were susceptible to newer NNRTIs such as Rilpivirine and Etravirine.

Background HIV genotyping has had a significant impact on the care and treatment of HIV/AIDS. At a clinical level, the test guides physicians on the choice of treatment regimens. At the surveillance level, it informs policy on consolidated treatment guidelines and microbial resistance control strategies. Until recently, the conventional test has utilized the Sanger sequencing (SS) method. Unlike Next Generation Sequencing (NGS), SS is limited by low data throughput and the inability of detecting low abundant drug-resistant variants. NGS can improve sensitivity and quantitatively identify low-abundance variants; in addition, it has the potential to improve efficiency as well as lowering costs when samples are batched. Despite the NGS benefits, its utilization in clinical drug resistance profiling is faced with mixed reactions. These are largely based on a lack of a consensus regarding the quality control strategy. Nonetheless, transitional views suggest validating the method against the gold-standard SS. Therefore, we present a validation report of an NGS-based in-house HIV genotyping method against the SS method in Uganda. Results Since there were no established proficiency test panels for NGS-based HIV genotyping, 15 clinical plasma samples for routine care were utilized. The use of clinical samples allowed for accuracy and precision studies. The workflow involved four main steps; viral RNA extraction, targeted amplicon generation, amplicon sequencing and data analysis. Accuracy of 98% with an average percentage error of 3% was reported for the NGS based assay against the SS platform demonstrating similar performance. The coefficient of variation (CV) findings for both the inter-run and inter-personnel precision showed no variability (CV ≤ 0%) at the relative abundance of ≥ 20%. For both inter-run and inter-personnel, a variation that affected the precision was observed at 1% frequency. Overall, for all the frequencies, CV registered a small range of (0–2%). Conclusion The NGS-based in-house HIV genotyping method fulfilled the minimum requirements that support its utilization for drug resistance profiling in a clinical setting of a low-income country. For more inclusive quality control studies, well-characterized wet panels need to be established.

Introduction Children and adolescents (0-19 years) living with HIV (CALHIV) in Uganda have historically had lower viral load suppression (VLS) rates than adults and this was partly attributed to sub-optimal antiretroviral therapy (ART) regimens. By June 2019, less than 50% of CALHIV were on optimal regimens despite appropriate policies in place. In July 2019, Ministry of Health (MOH) embarked on an ART optimization campaign to put all CALHIV on optimal regimens. We describe the process, challenges, and achievements during June 2019 – March 2021. Methods The campaign started in July 2019 and ART optimization was phased by age and by region due to ART stock shortage and gradually spread to the entire country with realization of sufficient stock. ART optimization referred to initiating or transitioning CALHIV on either an integrase strand transfer inhibitor(dolutegravir) or a protease inhibitor (Boosted lopinavir) as the anchor drug. Implementation of the campaign involved building capacity for ART optimization for all stakeholders and weekly use of robust data to monitor progress and make timely interventions along with regular supervision and onsite mentorships. MOH developed indicators on optimization which the implementing partners reported at weekly meetings facilitated by the MOH. A data call was made at end of March 2021 to determine the progress on ART optimization of CALHIV in Uganda and VLS analysis was done to assess the early impact of ART optimization. Results Adolescents comprised the majority (40,931/ 64,723; 63.2%) of CALHIV in HIV care by March 2021. Almost all (63,053/64,723; 97.4%) of CALHIV had been transitioned to optimal ART regimens. Despite the successful ART optimization for CALHIV, viral load suppression increased just slightly and remained suboptimal (<95%) by March 2021. Conclusions Proper preparation and timely data use for decision making enabled Uganda to succeed at ART optimization for almost all CALHIV amidst the COVID19 pandemic. However, ART optimization alone was not sufficient to have optimal viral load suppression nationally.

BackgroundHIV genotyping has had a significant impact on care and treatment of HIV/AIDS. At clinical level, the test guides physicians on the choice of treatment regimens. At surveillance level, it informs policy on consolidated treatment guidelines and microbial resistance control strategies. Until recently, the conventional test has utilized Sanger sequencing (SS) method. Unlike Next Generation Sequencing (NGS), SS is limited by low data throughput and the inability of detecting low abundant drug resistant variants. NGS has the capacity to improve sensitivity and quantitatively identify low-abundance variants; in addition, it has the potential to improve efficiency as well as lowering costs when samples are batched. Despite the NGS benefits, its utilization in clinical drug resistance profiling is faced with mixed reactions. These are largely based on lack of a consensus regarding the quality control strategy. Nonetheless, transitional views suggest validating the method against the gold-standard SS. Therefore, we present a validation report of an NGS-based in-house HIV genotyping method against SS method in Uganda. ResultsSince there were no established proficiency test panels for NGS-based HIV genotyping, fifteen (15) clinical plasma samples for routine care were utilized. The use of clinical samples allowed for accuracy and precision studies. The workflow involved four (4) main steps; viral RNA extraction, targeted amplicon generation, amplicon sequencing and data analysis. Accuracy of 98% with an average percentage error of 3% was reported for the NGS based assay against the SS platform demonstrating similar performance. The coefficient of variation (CV) findings for both the inter-run and inter-personnel precision showed no variability (CV ≤0%) at the relative abundance of ≥20%. For both inter-run and inter-personnel, variation that affected the precision was observed at 1% frequency. Overall, for all the frequencies, CV registered a small range of (0-2%).Conclusion The NGS-based in-house HIV genotyping method fulfilled the minimum requirements that support its utilization for drug resistance profiling in a clinical setting of a low-income country. For more inclusive quality control studies, well characterized wet panels need to be established.