Emerging HIV-1 Drug Resistance during Persistent Low-Level Viremia is Associated with Elevated Viral loads among Individuals on First-line Antiretroviral Therapy in Uganda

Emerging HIV-1 Drug Resistance during Persistent Low-Level Viremia is Associated with Elevated Viral loads among Individuals on First-line Antiretroviral Therapy in Uganda | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Emerging HIV-1 Drug Resistance during Persistent Low-Level Viremia is Associated with Elevated Viral loads among Individuals on First-line Antiretroviral Therapy in Uganda Sanyu Grace, Yunia Mayanja, Jonah Omooja, Juliet Nkungwa Asio, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7736362/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Background Although persistent low-level viremia (PLLV) has been associated with treatment failure, there is limited data about HIV drug resistance (HIVDR) during PLLV among Ugandans living with HIV. This study assessed HIVDR prevalence, patterns and associated factors among individuals on HIV-1 first-line ART who were experiencing PLLV. Methods A cross-sectional study among individuals with PLLV defined by two consecutive detectable viral load results < 1000 copies/mL and whose adherence scores were ≥ 95% over a twelve-month period. At 12 months, plasma samples of 444 eligible individuals on first-line ART were retrieved. HIVDR genotyping was performed on the protease, reverse transcriptase, and integrase regions of the HIV genome, and factors associated with HIVDR were assessed by logistic regression. Results Of the 444 individuals analyzed, only 67 (15.1%) were successfully genotyped. HIVDR prevalence was detected in 62.1% of those genotyped. Based on antiretroviral therapy (ART) drug classes, 56.1% of individuals in this study had HIVDR to NNRTIs, 42.2% to NRTIs, and 1.5% to both INSTIs and PIs. The most prevalent NRTI drug resistance mutations (DRMs) were M184V/I (40.3%) and K65R (14.9%). The NNRTI K103E/N/S and G190A mutations existed among 30% and 19.4% of individuals, respectively. The INSTI mutations N155H and R263K, together with the PI mutation M46I, were detected in < 2% of the population. Having an elevated viral load (VL between 500 and 999 copies/mL) (aOR: 6.4; 95% CI: (1.49–27.89); p = 0.01) and being below 25 years of age (aOR: 0.13; 95% CI (0.02–0.73); p = 0.02) were factors significantly associated with HIVDR during PLLV. Conclusion We report emerging HIVDR among individuals on first-line ART despite persistent low-level viremia and good drug adherence. HIVDR was associated with elevated PLLV (viral load ranges between 500 and 999 copies/mL) and young age. HIVDR genotyping for individuals on first-line ART experiencing elevated PLLV is highly recommended. Low genotyping success rates present a major impediment to HIVDR studies among individuals with PLLV, suggesting a need to adopt robust next-generation platforms for deep sequencing. Also, HIV intervention programs targeted toward the youth may positively impact HIV control. HIV-1 HIV-1 drug resistance persistent low-level viremia first-line antiretroviral therapy HIV-1 genotyping Figures Figure 1 Figure 2 Introduction By the end of 2024, of the 40.8 million people living with HIV (PLHIV) globally, 87% knew their HIV status. About 89% of those with known HIV status were receiving antiretroviral therapy (ART) with 94% of those on ART having suppressed viral loads 1 . HIV antiretroviral therapy (ART) is the bedrock of HIV treatment that has undoubtedly reduced the morbidity and mortality associated with HIV and related conditions. The purpose of ART is to suppress HIV viral replication so that the quantity of HIV circulating in the blood (viral load (VL)) is too low to be detected by HIV tests (undetectable) 2 . Effective ART therefore improves the health and increases the lifespan of those living with HIV, and through viral suppression, ART also prevents transmission of HIV 3 . It is widely believed that individuals with undetectable viral load do not transmit HIV to their HIV-negative sexual partners: This is referred to as undetectable = untransmissible (U = U) 4 . HIV viral suppression is a measure of ART success. The UNAIDS targets 95% of individuals on HIV ART attaining virological suppression if the goal of eliminating the global threat posed by HIV is to be realized by 2030. HIV-1 replicates mainly in CD4 + T-cells and is shed into blood plasma, thus the quantity of HIV-1 particles in plasma is a key marker to ART response. Effective ART can suppress viral replication to below 50 copies/mL and confer prolonged and healthy lives to PLHIV 5 . The WHO recommends VL monitoring for PLHIV on ART every 6 months with a threshold of VL ≥ 1000 copies per ml to indicate virologic failure 6 . There is evidence of treatment failure among individuals with the WHO-standard virologic suppression VL < 1000 copies/mL 7,8 . In Europe, PLHIV with a VL ≥ 50copies per ml are experiencing virologic failure and a regimen switch is recommended. Virologic failure in the USA is when PLHIV have a VL ≥ 200 copies/ml. While ART can suppress viral replication to below 50 copies/mL, some PLHIV still experience viremia without meeting the criteria for virologic failure depending on the setting 9 , a phenomenon known as persistent low-level viremia (PLLV). The WHO range for PLLV is plasma VL of 50 to 999 copies/mL 10 , the USA guidelines specify a range of 50 to 200 copies/mL, while the European standards define PLLV as VL of between 20 to 50 copies/mL 11 . In Uganda, PLLV is defined by two consecutive detectable viral load results < 1000copies/mL among individuals with an adherence score ≥ 95% over a twelve-month period 12 . The prevalence of low-level viremia (LLV) ranges from 2.7% to 13.7% in resource-rich settings where LLV is defined as VL between 20 and 200 copies/mL 13–15 . Studies carried out in sub-Sharan Africa have reported LLV prevalence of 8.2% in Uganda 16 , 18.5% in Kenya 17 , 13.9% in Cameroon 18 , 16% in Nigeria 19 , and between 2–20% in a multicenter study involving Kenya, Uganda, Tanzania and Nigeria 20 . The impact of Persistent low-level viremia on HIV-1 treatment outcomes is still debatable. Some studies in resource-rich settings have reported that PLLV increases the risk of subsequent virological failure 13 , 14 , 21 , 22 . Similarly, studies done is sub-Saharan Africa also reported that PLLV as a predictor for virologic non-suppression and treatment failure 16 , 17 , 19 , 20 . Concerningly, PLLV has also been associated with emergence of HIV drug resistance 15 , 23 , 24 . The 2020 World Health Organization (WHO) survey guidelines recommend the use of a laboratory-based approach leveraging remnant viral load samples with viral load ≥ 1000 copies per ml to conduct HIVDR testing in resource limited settings 25 . In Uganda, several threshold surveys conducted describe the prevalence and pattern of HIVDR among PLHIV experiencing virological failure (viral load ≥ 1000 copies/mL) 26–29 . In the US, clinical practice guidelines for HIV/AIDS recommend HIVDR testing for individuals with suboptimal viral suppression 30 . Uganda treatment guidelines recommend routine HIVDR only among patients on second line ART with two consecutive viral load (VL) determinations ≥ 1000 copies per mL performed 6 months apart 31 . Individuals on first-line ART are only switched to second line ART after intensive adherence counselling coupled with two consecutive viral load determinations ≥ 1000 copies per mL performed six months apart 31 . Therefore, individuals on first-line ART and those with low-level viremia (detectable viral load results < 1000copies/mL) are currently not eligible for HIVDR testing. Although PLLV has been associated with HIVDR, there is limited data about HIVDR among PLHIV that experience periods of persistent low-level viremia. This study assessed prevalence, mutation patterns and factors associated with HIVDR among individuals experiencing PLLV during first-line ART in Uganda. Methods Study design, population and setting In this cross-sectional study, we assessed HIVDR among 444 eligible individuals on first-line ART who had two consecutive VL results obtained 6 months apart between 1st July 2020 and 30th July 2021. In Uganda, this was the period of transition from non-nucleoside reverse transcriptase inhibitor (NNRTI)-based first-line regimens to dolutegravir (DTG)-based first-line and results from routine VL testing performed at 6 months-intervals were used to determine who should be switched to DTG 31 . We used the laboratory information management system (LIMS) to identify individuals who had experienced PLLV (detectable viral load < 1000 copies/mL on two consecutive VL tests among individuals having and adherence score ≥ 95% at both tests). Sampling procedures Plasma samples collected for the second viral load test were retrieved from − 80ᵒC storage from the Central public health laboratory (CPHL) biorepository, Kampala. CPHL is under the Uganda National Health and Diagnostic Laboratories (UNHLDS), a ministry of health department in charge of the national HIV viral load monitoring program. All available remnant plasma samples (560) with linked baseline to endpoint viral load results and matching epidemiological data within this period were retrieved. The following samples were excluded: all plasma samples with inadequate sample volume (< 1000µl), visible hemolysis (not viable for HIVDR testing), unmatched epidemiological data between records and missing epidemiological data between records. In total, plasma samples of 444 individuals were retrieved, packaged in dry ice within a cool box and transferred within two hours to the WHO-designated HIVDR laboratory at the Medical Research Council (MRC) /Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Uganda research unit in Entebbe, Uganda, for genotyping. HIV genotypic resistance testing The laboratory procedures for this study have previously been described 29 . Briefly, a 5-fold viral RNA concentration was achieved through ultra-centrifugation (50,000×g, 4ᵒc, 1hour) of the plasma samples (volume: 1000µl) and re-suspension of the pellet in 200µl of supernatant. Using the QIAGEN viral RNA extraction kit (QIAGEN, Hilden, Germany), we extracted HIV RNA from 140µl of plasma; and performed reverse transcription and complementary DNA synthesis using the superscript III high-fidelity one step PCR kit (Invitrogen). This was followed by a nested PCR, sequencing the HIV-1 complete protease gene (1–99 amino acids) and reverse transcriptase gene (1-252 amino acids). Among samples obtained from PLHIV taking a dolutegravir based ART regimen, we performed nested PCR and sequencing of the integrase gene (1-288 amino acids). The resulting chromatograms were base called using a customized RECall software 32 . As a means of quality control, our virology laboratory subscribes to the virology quality assurance (VQA) programme: We examined all sequences generated in the laboratory to ensure no cross-contamination by creating maximum-likelihood phylogenetic trees with 1000 bootstraps using RaxML 33 . We analysed sequences that passed the VQA test for HIVDR using the Stanford HIV database 34 . All sequences obtained have been deposited in GenBank under accession numbers PX308151-PX308176 and PX313797-PX313845 Study variables The dependent variable of interest was HIVDR at Persistent Low-Level Viremia. The independent variables included sex, age at second viral load test, duration on ART, ART regimen, viral load and HIV-1 subgroup. Data collection We sought permission from the Ugandan MOH to retrieve individual data from the laboratory information management system (LIMS) at the UNHDLs. The data was extracted into excel sheets, verified against data captured within the viral load request form, and any missing data was double-checked prior to analyses. Socio-demographic data, clinical data and sample identification information was collected. Data analysis Participant data was summarized into socio-demographic, clinical, and virological data with descriptive statistics (means and standard deviations for normally distributed data, or otherwise, medians and interquartile ranges (IQR) for skewed data) for continuous variables. For categorical outcomes, we used frequencies, proportions, and percentages. Where necessary, 95% confidence intervals were determined. We assessed associations between categorical variables using chi-squares and Fisher’s exact test. To assess the factors associated with acquired HIVDR during PLLV, we performed logistic regression in both univariate and multivariate models. A bivariate analysis was performed with each independent variable against the acquired HIVDR. All explanatory variables with a p-value ≤ 0.02 in bivariate models were entered in multivariate model in a stepwise manner to determine independent factors associated with acquired HIVDR at a significant p-value < 0.05 after adjusted analysis. Sex and age were always included in the models as they are known confounders. The assessed independent variables included sex, age, ART regimen, viral load, duration on ART, and HIV-1 subtype. Results The study flow chart in Fig. 1 summarizes the genotyping outcome of the 444 samples tested. Participant sample characteristics at the time of PLLV Among the 67 individual samples successfully genotyped, 70.1% (47) were from women. Majority of the samples (55.2%) were from individuals that resided within the central region of Uganda. In addition to this, a higher proportion (67.2%) of individuals were ≥ 25 years with a median age of 36 (IQR, 15). The median time on ART was 77.5 months (IQR, 80) whereas a larger proportion (52.2%) of individuals had been on ART for a period of < 72 months [mean, 29 (IQR, 42)]. Other details of the 67 successfully genotyped samples are summarized in Table 1 . Table 1 Characteristics of individuals with PLLV on first-line ART Characteristic n = 67 (%) Sex at birth Male 18 (26.9) Female 47 (70.1) Missing 2 (3.0) Region North 11 (16.4) East 12 (17.9) West 7 (10.5) Central 37 (55.2) Age, years, median (IQR) <25 [16 (4)] 22 (32.8) ≥25 [36 (15)] 45 (67.2) Time on ART in months, median (IQR) <72 [29 (42)] 35 (52.2) ≥72 [106.5 (42.5)] 32 (47.8) Viral load <500 39 (58.2) ≥500–999 28 (41.8) Subtype A 43 (64.1) B 4 (6.0) C 3 (4.5) D 17 (25.4) ART Drug regimen ABC-3TC-DTG 2 (3.0) AZT-3TC-NVP 7 (10.5) TDF-3TC-DTG 26 (38.8) TDF-3TC-EFV 31 (46.2) TDF-3TC-NVP 1 (1.5) Age was classified into young adults (< 25 years) and adults (≥ 25 years). Time on ART was classified into less than 6 years (< 72 months) and 6 years or more (≥ 72 months). Viral load was classified into two categories < 500 and ≥ 500–999. HIV-1 subtypes A, B, C and D were found. ABC, Abacavir; 3TC, Lamivudine, TDF, Tenofovir, DTG, Dolutegravir; NVP, Nevirapine; EFV, Efavirenz. Prevalence and patterns of surveillance HIVDR mutations (SDRMs) We observed HIVDR in 42/67 (62.7%) individuals with mutations spanning all the drug classes. A total of 38 (56.7%) individuals had mutations conferring resistance to NNRTIs, 26 (38.8%) had dual class (both NNRTI and NRTI) mutations, 29 (43.3%) had NRTI mutations and 1 (1.5%) had INSTI mutations. The most prevalent NRTI mutations were M184IV (64.3%), K65R (23.8%) and thymidine analogue mutations (TAMs) which were present in 19% of the individuals. The most prevalent NNRTI mutations were K103E/N (47.6%), G190A (38.1%) and G190GA (33.3%). Among the 28 samples successfully genotyped within the integrase region, two INSTI mutations N155H and R263K were found in one individual, thus a prevalence of 1.5% (Fig. 2 ). Factors associated with HIVDR among individuals with PLLV Viral load and age were independently associated with HIVDR. PLHIV with a higher viral load (VL = 500–999 copies per mL) were 6 times more likely to develop HIVDR during periods of PLLV (aOR: 6.4; 95% CI: (1.49–27.89; p = 0.01 ). PLHIV who were < 25 years old had 87% increased odds of developing HIVDR compared to those aged 25 years or older (aOR: 0.13; 95% CI (0.02–0.73; p = 0.02 ). In univariate analysis, being female correlated with HIVDR during PLLV; however, gender was not significantly associated with HIVDR after multivariate analysis (p = 0.05). Surprisingly, there was no significant association between the development of HIVDR during periods of PLLV and the ART regimen administered (DTG-based, NVP-based and EFV-based). (Table 2 ). Table 2 Factors associated with HIVDR among individuals with PLLV Characteristic Univariate Analysis Multivariate Analysis Any HIVDRMs (%) Crude OR (95% CI) P-Value (χ²) Adjusted OR (95% CI) P-Value (χ²) Sex at birth Male 7 (38.9) 1 1 Female 35 (74.5) 4.58 (1.45–14.51) 0.01 4.87 (1.04–22.87) 0.05 Age group in years < 25 19 (86.4) 1 1 ≥ 25 23 (51.1) 0.17 (0.04–0.64) 0.003 0.13 (0.02–0.73) 0.02 ART Regimen INT-based 15 (53.6) 1 1 NNRTI-based 27 (69.2) 1.95 (0.71–5.34) 0.19 1.94 (0.46–8.13) 0.37 Viral load range (cp/mL) < 500 19 (48.7) 1 1 ≥ 500–999 23 (82.1) 4.84 (1.53–15.34) 0.004 6.44 (1.49–27.89) 0.01 Duration on ART in months < 72 19 (54.3) 1 1 ≥ 72 23 (71.9) 2.15 (0.78–5.96) 0.14 1.59 (0.42–6.06) 0.5 HIV-1 Subtype A 28 (65.1) 1 1 B/C 5 (71.4) 1.34 (0.23–7.75) 1.31 (0.14–12.59 0.97 D 9 (52.9) 0.60 (0.38–1.89) 0.6 0.58 (0.13–2.54) 0.46 DTG, Dolutegravir; NVP, Nevirapine; EFV, Efavirenz. Statistically significant P values are shown in bold. We classified the age group into two categories, i.e. those < 20 and ≥ 20 years. The viral load range was classified into three categories: individuals with < 200 cp/mL, 200–499 cp/mL and 500–999 cp/mL. The duration on ART in months was classified into two categories, i.e. those with < 72 and ≥ 72 months. Individuals with HIV-1 subtype C were few therefore this variable was collapsed in the model. Discussion HIV ART has substantially contributed to increased virologic suppression rates globally with even higher rates expected following the introduction of more potent INSTIs such as Dolutegravir in first-line ART regimes. Nonetheless, some PLHIV on ART experience PLLV suggesting that the current ART regimens do not completely control viral replication beyond detection by current diagnostic technologies. In resource-constrained settings, HIVDR testing is rarely done for PLHIV experiencing PLLV. This study assessed prevalence, mutation patterns and explored factors associated with HIVDR among individuals experiencing PLLV while on first-line ART in Uganda. We report a high overall HIVDR prevalence of 62.7% among PLHIV experiencing PLLV while on first-line ART. A study done by Taramasso et al 15 revealed HIVDR prevalence of 85.7% in a large cohort in Genoa, Italy. Both these results were based on a small denominator of successfully genotyped samples. This could be attributed to low HIV genotyping success rates associated with low plasma viral loads 24 , 35 and suggests a need to adopt more robust sequencing technologies such as next-generation sequencing platform for sequencing LLV samples 7 . Studies in resource-rich settings reveal acquired HIVDR prevalence of 30% in France 36 , 35% in an European cohort 21 , and 20% in Spain 37 . These lower prevalences could be because their analyses were based on lower thresholds of VL < 500 copies/mL defining PLLV. Several studies have observed that HIVDR is associated with higher plasma viral loads and virological failure 23 , 38 . HIVDR in the state of PLLV in this study was mainly towards NRTIs and NNRTIs although resistance to PIs and INSTIs was detected. Similarly, a study in China based on a low-level viral load threshold of < 1000 reported the presence of HIV drug resistance to all drug classes 38 . The most prevalent HIVDR mutations observed here were the NRTIs M184V/I and K65R while the dominant NNRTIs were K103E/N, K101E, Y181C and G190A. This HIVDR profile is similar to profiles reported by other studies within our region 7 , 29 , 39 where HIV ART regimens have been largely dependent on NRTIs and NNRTIs before the introduction of DTG 12 . The high HIVDR prevalence towards NNRTIs that we report is higher than the range of 4% -28% reported by WHO from surveillance studies conducted among people retained on first-line ART in Africa by 2017 40 . Our findings combined with the Uganda surveillance data revealed an HIVDR higher prevalence of NNRTI resistance therefore justify the use of Dolutegravir (DTG) in first-line ART 41 . The current recommendations therefore guide the use of two NRTIs co- administered with DTG first-line 42 . A low HIVDR prevalence of 1.5% was detected for INSTIs, which is probably due to the effectiveness of DTG in viral suppression as a result of higher potency, genetic barrier and tolerability 43 . But it is also possible that there is not yet much resistance given that the use of DTG- based regimens within this population is less than five years 44 . The low PI resistance could probably be because PIs are mainly used in second-class regimens in our setting 12 . Notably, there was an association between viral load (VL) and the development of HIVDR among individuals from PLHIV with a viral load range of 500–999 copies/mL. Evidence from a study by 45 has shown an association between virological failure and HIVDR. Basing on the current Ugandan HIV treatment guidelines, 11/67 (16.4%) individuals with VL of 500–999 copies/mL in this study who had detectable HIVDR would not have been genotyped and would continue taking a failing ART regimen 12 . This increases the risk of progression to AIDS, reduction in ART regimen options, and transmission of HIV and HIV drug resistant variants. All these hinder the realization of the UNAIDS goal of ending the HIV/AIDs pandemic. Given that PLHIV probably developed HIVDR at thresholds > 500 copies /ml, there is a need to perform HIVDR testing for individuals with PLLV when VL ≥ 500 copies /ml. Some settings have already adopted HIVDR testing at more stringent PLLV thresholds of between 50 and 500 copies/mL 11,30 . Also, being a young adult was a risk factor for the emergence of HIVDR during PLLV in this study These findings corroborate those of other studies that young adults have poor adherence, low suppression rates, and likely to acquire HIVDR 45 , 46 . These findings should be interpreted with the following limitations in mind: Population sanger sequencing that we used may not reveal HIVDR mutations at viral load thresholds below 20% when compared to the Illumina NGS sequencing platform that expands the HIVDR profile among individuals on first-line ART 7 . Since we used sanger sequencing, the prevalence reported here may be lower than the actual prevalence of HIVDR in this population. In addition to this, we only successfully sequenced 67/444 (15.1%) of samples with PLLV. This reduced the number of individuals for HIVDR genotyping and subsequently reduced the power of this study. Despite those caveats, this is to the best of our knowledge one of only a few studies to assess HIVDR among individuals with PLLV in Uganda. The findings herein remain applicable in many settings as we have shown that even at LLV, there is a possibility of individuals harboring HIV drug resistance mutations. Furthermore, we have demonstrated that it is possible to sequence low level viremia samples with a VL of at least 250 copies per mL. Conclusion We report emergence of HIVDR among individuals on first-line ART despite persistent low-level viremia and reported good adherence to ART. HIVDR was associated with a elevated PLLV (viral load ranges between 500 to 999 copies/mL). This evidence suggests a need for HIVDR genotyping for individuals with PLLV, especially for those with elevated PLLV viral load ranges. Lack of HIVDR monitoring for individuals with PLLV could increase the population HIV reservoir, viral shedding, risk of virological failure and HIVDR which can potentially jeopardize HIV treatment programs. The low genotyping success rates present a major impediment to HIVDR studies among individuals with PLLV suggesting a need to adopt robust deep sequencing next-generation sequencing platforms. Also, HIV intervention programs targeted toward the youth may positively impact toward HIV control. Abbreviations ART Antiretroviral therapy CPHL Central public health laboratory DTG Dolutegravir HIVDR HIV drug resistance LSHTM London School of Hygiene and Tropical Medicine MRC Medical Research Council NNRTI Non-nucleoside reverse transcriptase inhibitors NRTI Nucleoside reverse transcriptase inhibitors PLHIV People living with HIV PLLVPersistent low-level viremia U=U Undetectable = Untransmissible UNHDL Uganda National Health and Diagnostic Laboratories UVRI Uganda Virus Research Institute VL Viral load Declarations Ethics approval and consent to participate This study was conducted in accordance with the Helsinki declaration. Ethical approval to conduct this study was provided by the Uganda Virus Research Institute Research and Ethics Committee (UVRI REC-reference number GC/127/20/05/428), and the Uganda National Council for Science and Technology (UNCST) under reference number HS 1432. Informed consent to participate in the study was obtained from all participants, who also provided informed consent to storage, and to the use of their samples for future HIV-related research. Consent for publication All authors have read the draft manuscript and consented to its publication. Availability of data and materials The datasets generated and analysed during the current study are not publicly available due to restriction policies and data protection policies of the Uganda Virus Research Institute. However, datasets can be made available by the corresponding author on reasonable request and after approval of the UVRI Research Ethics Committee. All sequences obtained have been deposited in GenBank under accession numbers PX308151-PX308176 and PX313797-PX313845 . Competing interests The authors have none to declare. Funding This work was funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) that is under the MRC/DFID Concordat Agreement. Acknowledgements The authors acknowledge the UVRI and the Ugandan MOH contribution towards this work. GS acknowledges the training from the University of Nairobi’s “Building Capacity for Writing Scientific Manuscripts (UANDISHI)” Program at the Faculty of Health Sciences. Author contribution GS- study coordination, genotyping, manuscript writing and publication; YM- manuscript writing and publication; JO- manuscript writing and publication; JNA- data and statistical analysis; MN- genotyping; PS- data collection and sample retrieval; NH- data collection and sample retrieval; IS-MOH clearance; KCD-proposal and manuscript writing; PK-proposal and grant application; DS- study PI. References UNAIDS. Global HIV & AIDS statistics — Fact sheet | UNAIDS. 2025. 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HIV-1 drug resistance genotyping success rates and correlates of Dried-blood spots and plasma specimen genotyping failure in a resource-limited setting. BMC Infect Dis 2022; 22 : 474. Available at: https://doi.org/10.1186/s12879-022-07453-9. Accessed November 21, 2024. Delaugerre C, Gallien S, Flandre P, et al. Impact of Low-Level-Viremia on HIV-1 Drug-Resistance Evolution among Antiretroviral Treated-Patients. PLoS ONE 2012; 7 : e36673. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC3349708/. Accessed November 19, 2024. Pereira R, Ludwig DA, Mathew S, et al. Predicting Viral Failure in Human Immunodeficiency Virus Perinatally Infected Youth with Persistent Low-Level Viremia on Highly Active Antiretroviral Therapy. J Pediatr Infect Dis Soc 2019; 8 : 303–9. Available at: https://doi.org/10.1093/jpids/piy041. Accessed November 19, 2024. Liu P, You Y, Liao L, et al. Impact of low-level viremia with drug resistance on CD4 cell counts among people living with HIV on antiretroviral treatment in China. BMC Infect Dis 2022; 22 : 1–10. Segujja F, Omooja J, Lunkuse S, et al. High Levels of Acquired HIV Drug Resistance Following Virological Nonsuppression in HIV-Infected Women from a High-Risk Cohort in Uganda. AIDS Res Hum Retroviruses 2020; 36 : 782–91. Available at: https://login.research4life.org/tacsgr1www_liebertpub_com/doi/10.1089/aid.2019.0279. Accessed October 12, 2020. WHO. Preventing and Responding to HIV Drug Resistance in the African Region . 2019. Watera C, Ssemwanga D, Namayanja G, et al. HIV drug resistance among adults initiating antiretroviral therapy in Uganda. J Antimicrob Chemother 2021; 76 : 2407–14. MOH. Ministry of Health CONSOLIDATED GUIDELINES FOR PREVENTION. 2018; 2 : 2016–9. Günthard HF, Saag MS, Benson CA, et al. Antiretroviral Drugs for Treatment and Prevention of HIV Infection in Adults: 2016 Recommendations of the International Antiviral Society-USA Panel. JAMA 2016; 316 : 191–210. WHO. HIV drug resistance: brief report 2024 . 2024. Omooja J, Nannyonjo M, Sanyu G, et al. Rates of HIV-1 virological suppression and patterns of acquired drug resistance among fisherfolk on first-line antiretroviral therapy in Uganda. J Antimicrob Chemother 2019; 74 : 3021–9. Nega J, Taye S, Million Y, Rodrigo C, Eshetie S. Antiretroviral treatment failure and associated factors among HIV patients on first-line antiretroviral treatment in Sekota, northeast Ethiopia. AIDS Res Ther 2020; 17 : 39. Available at: https://doi.org/10.1186/s12981-020-00294-z. Accessed October 12, 2021. Additional Declarations No competing interests reported. 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11:19:35","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":119708,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7736362/v1/63032b6f8e8d0fbaa3c599d9.html"},{"id":94187723,"identity":"c9043077-9162-4473-aac9-c4085b97f827","added_by":"auto","created_at":"2025-10-23 11:19:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":114320,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy flow chart for individuals on first-line ART experiencing PLLV. \u003c/strong\u003ePrevalence for HIVDR to all classes were determined using the 67 successfully genotyped individuals as the denominator.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7736362/v1/e0eb79fe73c4d94de079fcc5.png"},{"id":94188367,"identity":"f9580914-a7eb-4a82-9dfb-b30d361bb159","added_by":"auto","created_at":"2025-10-23 11:27:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":127542,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of surveillance drug resistance mutations among individuals with HIVDR\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7736362/v1/bb01d0be79ee9ed0bc7794ab.png"},{"id":94188520,"identity":"9dbd4e9e-b5d2-4dc4-8a6a-bb4f34363a7c","added_by":"auto","created_at":"2025-10-23 11:35:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1245786,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7736362/v1/7c312cab-b7f1-4b26-b35e-49e9a6bb0660.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Emerging HIV-1 Drug Resistance during Persistent Low-Level Viremia is Associated with Elevated Viral loads among Individuals on First-line Antiretroviral Therapy in Uganda","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBy the end of 2024, of the 40.8\u0026nbsp;million people living with HIV (PLHIV) globally, 87% knew their HIV status. About 89% of those with known HIV status were receiving antiretroviral therapy (ART) with 94% of those on ART having suppressed viral loads\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. HIV antiretroviral therapy (ART) is the bedrock of HIV treatment that has undoubtedly reduced the morbidity and mortality associated with HIV and related conditions. The purpose of ART is to suppress HIV viral replication so that the quantity of HIV circulating in the blood (viral load (VL)) is too low to be detected by HIV tests (undetectable) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Effective ART therefore improves the health and increases the lifespan of those living with HIV, and through viral suppression, ART also prevents transmission of HIV\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. It is widely believed that individuals with undetectable viral load do not transmit HIV to their HIV-negative sexual partners: This is referred to as undetectable\u0026thinsp;=\u0026thinsp;untransmissible (U\u0026thinsp;=\u0026thinsp;U)\u003csup\u003e4\u003c/sup\u003e. HIV viral suppression is a measure of ART success. The UNAIDS targets 95% of individuals on HIV ART attaining virological suppression if the goal of eliminating the global threat posed by HIV is to be realized by 2030.\u003c/p\u003e\u003cp\u003eHIV-1 replicates mainly in CD4\u0026thinsp;+\u0026thinsp;T-cells and is shed into blood plasma, thus the quantity of HIV-1 particles in plasma is a key marker to ART response. Effective ART can suppress viral replication to below 50 copies/mL and confer prolonged and healthy lives to PLHIV\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The WHO recommends VL monitoring for PLHIV on ART every 6 months with a threshold of VL\u0026thinsp;\u0026ge;\u0026thinsp;1000 copies per ml to indicate virologic failure\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. There is evidence of treatment failure among individuals with the WHO-standard virologic suppression VL\u0026thinsp;\u0026lt;\u0026thinsp;1000 copies/mL\u003csup\u003e7,8\u003c/sup\u003e. In Europe, PLHIV with a VL\u0026thinsp;\u0026ge;\u0026thinsp;50copies per ml are experiencing virologic failure and a regimen switch is recommended. Virologic failure in the USA is when PLHIV have a VL\u0026thinsp;\u0026ge;\u0026thinsp;200 copies/ml. While ART can suppress viral replication to below 50 copies/mL, some PLHIV still experience viremia without meeting the criteria for virologic failure depending on the setting\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, a phenomenon known as persistent low-level viremia (PLLV). The WHO range for PLLV is plasma VL of 50 to 999 copies/mL\u003csup\u003e10\u003c/sup\u003e, the USA guidelines specify a range of 50 to 200 copies/mL, while the European standards define PLLV as VL of between 20 to 50 copies/mL\u003csup\u003e11\u003c/sup\u003e. In Uganda, PLLV is defined by two consecutive detectable viral load results\u0026thinsp;\u0026lt;\u0026thinsp;1000copies/mL among individuals with an adherence score\u0026thinsp;\u0026ge;\u0026thinsp;95% over a twelve-month period\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe prevalence of low-level viremia (LLV) ranges from 2.7% to 13.7% in resource-rich settings where LLV is defined as VL between 20 and 200 copies/mL\u003csup\u003e13\u0026ndash;15\u003c/sup\u003e. Studies carried out in sub-Sharan Africa have reported LLV prevalence of 8.2% in Uganda\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, 18.5% in Kenya\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, 13.9% in Cameroon\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, 16% in Nigeria\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, and between 2\u0026ndash;20% in a multicenter study involving Kenya, Uganda, Tanzania and Nigeria\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The impact of Persistent low-level viremia on HIV-1 treatment outcomes is still debatable. Some studies in resource-rich settings have reported that PLLV increases the risk of subsequent virological failure\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Similarly, studies done is sub-Saharan Africa also reported that PLLV as a predictor for virologic non-suppression and treatment failure\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Concerningly, PLLV has also been associated with emergence of HIV drug resistance\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe 2020 World Health Organization (WHO) survey guidelines recommend the use of a laboratory-based approach leveraging remnant viral load samples with viral load\u0026thinsp;\u0026ge;\u0026thinsp;1000 copies per ml to conduct HIVDR testing in resource limited settings \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In Uganda, several threshold surveys conducted describe the prevalence and pattern of HIVDR among PLHIV experiencing virological failure (viral load\u0026thinsp;\u0026ge;\u0026thinsp;1000 copies/mL)\u003csup\u003e26\u0026ndash;29\u003c/sup\u003e. In the US, clinical practice guidelines for HIV/AIDS recommend HIVDR testing for individuals with suboptimal viral suppression \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Uganda treatment guidelines recommend routine HIVDR only among patients on second line ART with two consecutive viral load (VL) determinations\u0026thinsp;\u0026ge;\u0026thinsp;1000 copies per mL performed 6 months apart \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Individuals on first-line ART are only switched to second line ART after intensive adherence counselling coupled with two consecutive viral load determinations\u0026thinsp;\u0026ge;\u0026thinsp;1000 copies per mL performed six months apart \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Therefore, individuals on first-line ART and those with low-level viremia (detectable viral load results\u0026thinsp;\u0026lt;\u0026thinsp;1000copies/mL) are currently not eligible for HIVDR testing. Although PLLV has been associated with HIVDR, there is limited data about HIVDR among PLHIV that experience periods of persistent low-level viremia. This study assessed prevalence, mutation patterns and factors associated with HIVDR among individuals experiencing PLLV during first-line ART in Uganda.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design, population and setting\u003c/h2\u003e\u003cp\u003eIn this cross-sectional study, we assessed HIVDR among 444 eligible individuals on first-line ART who had two consecutive VL results obtained 6 months apart between 1st July 2020 and 30th July 2021. In Uganda, this was the period of transition from non-nucleoside reverse transcriptase inhibitor (NNRTI)-based first-line regimens to dolutegravir (DTG)-based first-line and results from routine VL testing performed at 6 months-intervals were used to determine who should be switched to DTG \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. We used the laboratory information management system (LIMS) to identify individuals who had experienced PLLV (detectable viral load\u0026thinsp;\u0026lt;\u0026thinsp;1000 copies/mL on two consecutive VL tests among individuals having and adherence score\u0026thinsp;\u0026ge;\u0026thinsp;95% at both tests).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSampling procedures\u003c/h3\u003e\n\u003cp\u003ePlasma samples collected for the second viral load test were retrieved from \u0026minus;\u0026thinsp;80ᵒC storage from the Central public health laboratory (CPHL) biorepository, Kampala. CPHL is under the Uganda National Health and Diagnostic Laboratories (UNHLDS), a ministry of health department in charge of the national HIV viral load monitoring program. All available remnant plasma samples (560) with linked baseline to endpoint viral load results and matching epidemiological data within this period were retrieved. The following samples were excluded: all plasma samples with inadequate sample volume (\u0026lt;\u0026thinsp;1000\u0026micro;l), visible hemolysis (not viable for HIVDR testing), unmatched epidemiological data between records and missing epidemiological data between records. In total, plasma samples of 444 individuals were retrieved, packaged in dry ice within a cool box and transferred within two hours to the WHO-designated HIVDR laboratory at the Medical Research Council (MRC) /Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Uganda research unit in Entebbe, Uganda, for genotyping.\u003c/p\u003e\n\u003ch3\u003eHIV genotypic resistance testing\u003c/h3\u003e\n\u003cp\u003eThe laboratory procedures for this study have previously been described\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Briefly, a 5-fold viral RNA concentration was achieved through ultra-centrifugation (50,000\u0026times;g, 4ᵒc, 1hour) of the plasma samples (volume: 1000\u0026micro;l) and re-suspension of the pellet in 200\u0026micro;l of supernatant. Using the QIAGEN viral RNA extraction kit (QIAGEN, Hilden, Germany), we extracted HIV RNA from 140\u0026micro;l of plasma; and performed reverse transcription and complementary DNA synthesis using the superscript III high-fidelity one step PCR kit (Invitrogen). This was followed by a nested PCR, sequencing the HIV-1 complete protease gene (1\u0026ndash;99 amino acids) and reverse transcriptase gene (1-252 amino acids). Among samples obtained from PLHIV taking a dolutegravir based ART regimen, we performed nested PCR and sequencing of the integrase gene (1-288 amino acids). The resulting chromatograms were base called using a customized RECall software \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. As a means of quality control, our virology laboratory subscribes to the virology quality assurance (VQA) programme: We examined all sequences generated in the laboratory to ensure no cross-contamination by creating maximum-likelihood phylogenetic trees with 1000 bootstraps using RaxML\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. We analysed sequences that passed the VQA test for HIVDR using the Stanford HIV database\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. All sequences obtained have been deposited in GenBank under accession numbers \u003cb\u003ePX308151-PX308176\u003c/b\u003e and \u003cb\u003ePX313797-PX313845\u003c/b\u003e\u003c/p\u003e\n\u003ch3\u003eStudy variables\u003c/h3\u003e\n\u003cp\u003eThe dependent variable of interest was HIVDR at Persistent Low-Level Viremia. The independent variables included sex, age at second viral load test, duration on ART, ART regimen, viral load and HIV-1 subgroup.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eWe sought permission from the Ugandan MOH to retrieve individual data from the laboratory information management system (LIMS) at the UNHDLs. The data was extracted into excel sheets, verified against data captured within the viral load request form, and any missing data was double-checked prior to analyses. Socio-demographic data, clinical data and sample identification information was collected.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eParticipant data was summarized into socio-demographic, clinical, and virological data with descriptive statistics (means and standard deviations for normally distributed data, or otherwise, medians and interquartile ranges (IQR) for skewed data) for continuous variables. For categorical outcomes, we used frequencies, proportions, and percentages. Where necessary, 95% confidence intervals were determined. We assessed associations between categorical variables using chi-squares and Fisher\u0026rsquo;s exact test. To assess the factors associated with acquired HIVDR during PLLV, we performed logistic regression in both univariate and multivariate models. A bivariate analysis was performed with each independent variable against the acquired HIVDR. All explanatory variables with a p-value\u0026thinsp;\u0026le;\u0026thinsp;0.02 in bivariate models were entered in multivariate model in a stepwise manner to determine independent factors associated with acquired HIVDR at a significant p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 after adjusted analysis. Sex and age were always included in the models as they are known confounders. The assessed independent variables included sex, age, ART regimen, viral load, duration on ART, and HIV-1 subtype.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe study flow chart in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the genotyping outcome of the 444 samples tested.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eParticipant sample characteristics at the time of PLLV\u003c/h3\u003e\n\u003cp\u003eAmong the 67 individual samples successfully genotyped, 70.1% (47) were from women. Majority of the samples (55.2%) were from individuals that resided within the central region of Uganda. In addition to this, a higher proportion (67.2%) of individuals were \u0026ge;\u0026thinsp;25 years with a median age of 36 (IQR, 15). The median time on ART was 77.5 months (IQR, 80) whereas a larger proportion (52.2%) of individuals had been on ART for a period of \u0026lt;\u0026thinsp;72 months [mean, 29 (IQR, 42)]. Other details of the 67 successfully genotyped samples are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of individuals with PLLV on first-line ART\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;67 (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex at birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18 (26.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47 (70.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2 (3.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11 (16.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12 (17.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (10.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37 (55.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, years, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;25 [16 (4)]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22 (32.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;25 [36 (15)]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45 (67.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime on ART in months, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;72 [29 (42)]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35 (52.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;72 [106.5 (42.5)]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32 (47.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViral load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e39 (58.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;500\u0026ndash;999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28 (41.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43 (64.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4 (6.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3 (4.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17 (25.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eART Drug regimen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABC-3TC-DTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2 (3.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAZT-3TC-NVP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (10.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTDF-3TC-DTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26 (38.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTDF-3TC-EFV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31 (46.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTDF-3TC-NVP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1 (1.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAge was classified into young adults (\u0026lt;\u0026thinsp;25 years) and adults (\u0026ge;\u0026thinsp;25 years). Time on ART was classified into less than 6 years (\u0026lt;\u0026thinsp;72 months) and 6 years or more (\u0026ge;\u0026thinsp;72 months). Viral load was classified into two categories\u0026thinsp;\u0026lt;\u0026thinsp;500 and \u0026ge;\u0026thinsp;500\u0026ndash;999. HIV-1 subtypes A, B, C and D were found. ABC, Abacavir; 3TC, Lamivudine, TDF, Tenofovir, DTG, Dolutegravir; NVP, Nevirapine; EFV, Efavirenz.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePrevalence and patterns of surveillance HIVDR mutations (SDRMs)\u003c/h2\u003e\u003cp\u003eWe observed HIVDR in 42/67 (62.7%) individuals with mutations spanning all the drug classes. A total of 38 (56.7%) individuals had mutations conferring resistance to NNRTIs, 26 (38.8%) had dual class (both NNRTI and NRTI) mutations, 29 (43.3%) had NRTI mutations and 1 (1.5%) had INSTI mutations. The most prevalent NRTI mutations were M184IV (64.3%), K65R (23.8%) and thymidine analogue mutations (TAMs) which were present in 19% of the individuals. The most prevalent NNRTI mutations were K103E/N (47.6%), G190A (38.1%) and G190GA (33.3%). Among the 28 samples successfully genotyped within the integrase region, two INSTI mutations N155H and R263K were found in one individual, thus a prevalence of 1.5% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eFactors associated with HIVDR among individuals with PLLV\u003c/h2\u003e\u003cp\u003eViral load and age were independently associated with HIVDR. PLHIV with a higher viral load (VL\u0026thinsp;=\u0026thinsp;500\u0026ndash;999 copies per mL) were 6 times more likely to develop HIVDR during periods of PLLV (aOR: 6.4; 95% CI: (1.49\u0026ndash;27.89; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.01\u003c/b\u003e). PLHIV who were \u0026lt;\u0026thinsp;25 years old had 87% increased odds of developing HIVDR compared to those aged 25 years or older (aOR: 0.13; 95% CI (0.02\u0026ndash;0.73; \u003cb\u003ep\u0026thinsp;=\u0026thinsp;0.02\u003c/b\u003e). In univariate analysis, being female correlated with HIVDR during PLLV; however, gender was not significantly associated with HIVDR after multivariate analysis (p\u0026thinsp;=\u0026thinsp;0.05). Surprisingly, there was no significant association between the development of HIVDR during periods of PLLV and the ART regimen administered (DTG-based, NVP-based and EFV-based). (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFactors associated with HIVDR among individuals with PLLV\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eUnivariate Analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eMultivariate Analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAny HIVDRMs (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCrude OR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-Value (χ\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP-Value (χ\u0026sup2;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex at birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7 (38.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35 (74.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.58 (1.45\u0026ndash;14.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.87 (1.04\u0026ndash;22.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge group in years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19 (86.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23 (51.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.17 (0.04\u0026ndash;0.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.13 (0.02\u0026ndash;0.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eART Regimen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINT-based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15 (53.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNNRTI-based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27 (69.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.95 (0.71\u0026ndash;5.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.94 (0.46\u0026ndash;8.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViral load range (cp/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19 (48.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;500\u0026ndash;999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23 (82.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.84 (1.53\u0026ndash;15.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.44 (1.49\u0026ndash;27.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDuration on ART in months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19 (54.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23 (71.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.15 (0.78\u0026ndash;5.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.59 (0.42\u0026ndash;6.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHIV-1 Subtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28 (65.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB/C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5 (71.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.34 (0.23\u0026ndash;7.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.31 (0.14\u0026ndash;12.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (52.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.60 (0.38\u0026ndash;1.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.58 (0.13\u0026ndash;2.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eDTG, Dolutegravir; NVP, Nevirapine; EFV, Efavirenz. Statistically significant P values are shown in bold. We classified the age group into two categories, i.e. those\u0026thinsp;\u0026lt;\u0026thinsp;20 and \u0026ge;\u0026thinsp;20 years. The viral load range was classified into three categories: individuals with \u0026lt;\u0026thinsp;200 cp/mL, 200\u0026ndash;499 cp/mL and 500\u0026ndash;999 cp/mL. The duration on ART in months was classified into two categories, i.e. those with \u0026lt;\u0026thinsp;72 and \u0026ge;\u0026thinsp;72 months. Individuals with HIV-1 subtype C were few therefore this variable was collapsed in the model.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHIV ART has substantially contributed to increased virologic suppression rates globally with even higher rates expected following the introduction of more potent INSTIs such as Dolutegravir in first-line ART regimes. Nonetheless, some PLHIV on ART experience PLLV suggesting that the current ART regimens do not completely control viral replication beyond detection by current diagnostic technologies. In resource-constrained settings, HIVDR testing is rarely done for PLHIV experiencing PLLV. This study assessed prevalence, mutation patterns and explored factors associated with HIVDR among individuals experiencing PLLV while on first-line ART in Uganda.\u003c/p\u003e\u003cp\u003eWe report a high overall HIVDR prevalence of 62.7% among PLHIV experiencing PLLV while on first-line ART. A study done by Taramasso et al\u003csup\u003e15\u003c/sup\u003e revealed HIVDR prevalence of 85.7% in a large cohort in Genoa, Italy. Both these results were based on a small denominator of successfully genotyped samples. This could be attributed to low HIV genotyping success rates associated with low plasma viral loads \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e and suggests a need to adopt more robust sequencing technologies such as next-generation sequencing platform for sequencing LLV samples\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Studies in resource-rich settings reveal acquired HIVDR prevalence of 30% in France \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, 35% in an European cohort\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and 20% in Spain\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. These lower prevalences could be because their analyses were based on lower thresholds of VL\u0026thinsp;\u0026lt;\u0026thinsp;500 copies/mL defining PLLV. Several studies have observed that HIVDR is associated with higher plasma viral loads and virological failure\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHIVDR in the state of PLLV in this study was mainly towards NRTIs and NNRTIs although resistance to PIs and INSTIs was detected. Similarly, a study in China based on a low-level viral load threshold of \u0026lt;\u0026thinsp;1000 reported the presence of HIV drug resistance to all drug classes\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. The most prevalent HIVDR mutations observed here were the NRTIs M184V/I and K65R while the dominant NNRTIs were K103E/N, K101E, Y181C and G190A. This HIVDR profile is similar to profiles reported by other studies within our region\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e where HIV ART regimens have been largely dependent on NRTIs and NNRTIs before the introduction of DTG\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The high HIVDR prevalence towards NNRTIs that we report is higher than the range of 4% -28% reported by WHO from surveillance studies conducted among people retained on first-line ART in Africa by 2017 \u003csup\u003e40\u003c/sup\u003e. Our findings combined with the Uganda surveillance data revealed an HIVDR higher prevalence of NNRTI resistance therefore justify the use of Dolutegravir (DTG) in first-line ART \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. The current recommendations therefore guide the use of two NRTIs co- administered with DTG first-line\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. A low HIVDR prevalence of 1.5% was detected for INSTIs, which is probably due to the effectiveness of DTG in viral suppression as a result of higher potency, genetic barrier and tolerability\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. But it is also possible that there is not yet much resistance given that the use of DTG- based regimens within this population is less than five years \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. The low PI resistance could probably be because PIs are mainly used in second-class regimens in our setting\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNotably, there was an association between viral load (VL) and the development of HIVDR among individuals from PLHIV with a viral load range of 500\u0026ndash;999 copies/mL. Evidence from a study by \u003csup\u003e45\u003c/sup\u003e has shown an association between virological failure and HIVDR. Basing on the current Ugandan HIV treatment guidelines, 11/67 (16.4%) individuals with VL of 500\u0026ndash;999 copies/mL in this study who had detectable HIVDR would not have been genotyped and would continue taking a failing ART regimen\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. This increases the risk of progression to AIDS, reduction in ART regimen options, and transmission of HIV and HIV drug resistant variants. All these hinder the realization of the UNAIDS goal of ending the HIV/AIDs pandemic. Given that PLHIV probably developed HIVDR at thresholds\u0026thinsp;\u0026gt;\u0026thinsp;500 copies /ml, there is a need to perform HIVDR testing for individuals with PLLV when VL\u0026thinsp;\u0026ge;\u0026thinsp;500 copies /ml. Some settings have already adopted HIVDR testing at more stringent PLLV thresholds of between 50 and 500 copies/mL\u003csup\u003e11,30\u003c/sup\u003e. Also, being a young adult was a risk factor for the emergence of HIVDR during PLLV in this study These findings corroborate those of other studies that young adults have poor adherence, low suppression rates, and likely to acquire HIVDR\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThese findings should be interpreted with the following limitations in mind: Population sanger sequencing that we used may not reveal HIVDR mutations at viral load thresholds below 20% when compared to the Illumina NGS sequencing platform that expands the HIVDR profile among individuals on first-line ART\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Since we used sanger sequencing, the prevalence reported here may be lower than the actual prevalence of HIVDR in this population. In addition to this, we only successfully sequenced 67/444 (15.1%) of samples with PLLV. This reduced the number of individuals for HIVDR genotyping and subsequently reduced the power of this study.\u003c/p\u003e\u003cp\u003eDespite those caveats, this is to the best of our knowledge one of only a few studies to assess HIVDR among individuals with PLLV in Uganda. The findings herein remain applicable in many settings as we have shown that even at LLV, there is a possibility of individuals harboring HIV drug resistance mutations. Furthermore, we have demonstrated that it is possible to sequence low level viremia samples with a VL of at least 250 copies per mL.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe report emergence of HIVDR among individuals on first-line ART despite persistent low-level viremia and reported good adherence to ART. HIVDR was associated with a elevated PLLV (viral load ranges between 500 to 999 copies/mL). This evidence suggests a need for HIVDR genotyping for individuals with PLLV, especially for those with elevated PLLV viral load ranges. Lack of HIVDR monitoring for individuals with PLLV could increase the population HIV reservoir, viral shedding, risk of virological failure and HIVDR which can potentially jeopardize HIV treatment programs. The low genotyping success rates present a major impediment to HIVDR studies among individuals with PLLV suggesting a need to adopt robust deep sequencing next-generation sequencing platforms. Also, HIV intervention programs targeted toward the youth may positively impact toward HIV control.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eART Antiretroviral therapy\u003c/p\u003e\n\u003cp\u003eCPHL Central public health laboratory\u003c/p\u003e\n\u003cp\u003eDTG Dolutegravir\u003c/p\u003e\n\u003cp\u003eHIVDR HIV drug resistance\u003c/p\u003e\n\u003cp\u003eLSHTM London School of Hygiene and Tropical Medicine\u003c/p\u003e\n\u003cp\u003eMRC Medical Research Council\u003c/p\u003e\n\u003cp\u003eNNRTI Non-nucleoside reverse transcriptase inhibitors\u003c/p\u003e\n\u003cp\u003eNRTI Nucleoside reverse transcriptase inhibitors\u003c/p\u003e\n\u003cp\u003ePLHIV People living with HIV\u003c/p\u003e\n\u003cp\u003ePLLVPersistent low-level viremia\u003c/p\u003e\n\u003cp\u003eU=U Undetectable = Untransmissible\u003c/p\u003e\n\u003cp\u003eUNHDL Uganda National Health and Diagnostic Laboratories\u003c/p\u003e\n\u003cp\u003eUVRI Uganda Virus Research Institute\u003c/p\u003e\n\u003cp\u003eVL Viral load\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Helsinki declaration. Ethical approval to conduct this study was provided by the Uganda Virus Research Institute Research and Ethics Committee (UVRI REC-reference number GC/127/20/05/428), and the Uganda National Council for Science and Technology (UNCST) under reference number HS 1432. Informed consent to participate in the study was obtained from all participants, who also provided informed consent to storage, and to the use of their samples for future HIV-related research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read the draft manuscript and consented to its publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are not publicly available due to restriction policies and data protection policies of the Uganda Virus Research Institute. However, datasets can be made available by the corresponding author on reasonable request and after approval of the UVRI Research Ethics Committee.\u0026nbsp;All sequences obtained have been deposited in GenBank under accession numbers \u003cstrong\u003ePX308151-PX308176\u003c/strong\u003e and \u003cstrong\u003ePX313797-PX313845\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have none to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) that is under the MRC/DFID Concordat Agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the UVRI and the Ugandan MOH contribution towards this work. GS acknowledges\u0026nbsp;the training from the University of Nairobi\u0026rsquo;s \u0026ldquo;Building Capacity for Writing Scientific Manuscripts (UANDISHI)\u0026rdquo; Program at the Faculty of Health Sciences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGS- study coordination, genotyping, manuscript writing and publication; YM- manuscript writing and publication; JO- manuscript writing and publication; JNA- data and statistical analysis; MN- genotyping; PS- data collection and sample retrieval; NH- data collection and sample retrieval; IS-MOH clearance; KCD-proposal and manuscript writing; PK-proposal and grant application; DS- study PI.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUNAIDS. Global HIV \u0026amp; AIDS statistics \u0026mdash; Fact sheet | UNAIDS. 2025. Available at: https://www.unaids.org/en/resources/fact-sheet. 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Accessed October 12, 2021.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HIV-1, HIV-1 drug resistance, persistent low-level viremia, first-line antiretroviral therapy, HIV-1 genotyping","lastPublishedDoi":"10.21203/rs.3.rs-7736362/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7736362/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAlthough persistent low-level viremia (PLLV) has been associated with treatment failure, there is limited data about HIV drug resistance (HIVDR) during PLLV among Ugandans living with HIV. This study assessed HIVDR prevalence, patterns and associated factors among individuals on HIV-1 first-line ART who were experiencing PLLV.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional study among individuals with PLLV defined by two consecutive detectable viral load results\u0026thinsp;\u0026lt;\u0026thinsp;1000 copies/mL and whose adherence scores were \u0026ge;\u0026thinsp;95% over a twelve-month period. At 12 months, plasma samples of 444 eligible individuals on first-line ART were retrieved. HIVDR genotyping was performed on the protease, reverse transcriptase, and integrase regions of the HIV genome, and factors associated with HIVDR were assessed by logistic regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf the 444 individuals analyzed, only 67 (15.1%) were successfully genotyped. HIVDR prevalence was detected in 62.1% of those genotyped. Based on antiretroviral therapy (ART) drug classes, 56.1% of individuals in this study had HIVDR to NNRTIs, 42.2% to NRTIs, and 1.5% to both INSTIs and PIs. The most prevalent NRTI drug resistance mutations (DRMs) were M184V/I (40.3%) and K65R (14.9%). The NNRTI K103E/N/S and G190A mutations existed among 30% and 19.4% of individuals, respectively. The INSTI mutations N155H and R263K, together with the PI mutation M46I, were detected in \u0026lt;\u0026thinsp;2% of the population. Having an elevated viral load (VL between 500 and 999 copies/mL) (aOR: 6.4; 95% CI: (1.49\u0026ndash;27.89); p\u0026thinsp;=\u0026thinsp;0.01) and being below 25 years of age (aOR: 0.13; 95% CI (0.02\u0026ndash;0.73); p\u0026thinsp;=\u0026thinsp;0.02) were factors significantly associated with HIVDR during PLLV.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eWe report emerging HIVDR among individuals on first-line ART despite persistent low-level viremia and good drug adherence. HIVDR was associated with elevated PLLV (viral load ranges between 500 and 999 copies/mL) and young age. HIVDR genotyping for individuals on first-line ART experiencing elevated PLLV is highly recommended. Low genotyping success rates present a major impediment to HIVDR studies among individuals with PLLV, suggesting a need to adopt robust next-generation platforms for deep sequencing. Also, HIV intervention programs targeted toward the youth may positively impact HIV control.\u003c/p\u003e","manuscriptTitle":"Emerging HIV-1 Drug Resistance during Persistent Low-Level Viremia is Associated with Elevated Viral loads among Individuals on First-line Antiretroviral Therapy in Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 11:19:30","doi":"10.21203/rs.3.rs-7736362/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-12T07:29:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-06T18:18:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143170141146337535465002719978800562831","date":"2026-01-05T12:26:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306939978289623660566212942410749919132","date":"2026-01-05T07:02:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55143831300687600863631441604700650116","date":"2025-12-17T13:37:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280023194053739277486623942815943182550","date":"2025-12-08T14:41:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-07T08:13:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215066131338498617233656572043700873724","date":"2025-12-06T10:39:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195751451228093701454585935893963445793","date":"2025-12-05T12:04:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"148509425482518894340977591934886029225","date":"2025-11-04T12:41:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T20:29:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-09T20:26:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-09T06:56:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-08T16:49:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-10-08T16:46:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3c57cfad-57cc-43f8-8f7c-185ed4a9e9fe","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T09:38:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-23 11:19:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7736362","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7736362","identity":"rs-7736362","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}