Abstract
Objectives
This study aimed to evaluate the prevalence and characteristics of drug resistance mutations (DRMs) in patients with low-level viremia (LLV) in Southwestern China, as it has become a growing challenge in AIDS clinical practice.
Methods
This cross-sectional study was performed in Yunnan Province, Southwestern China. LLV was defined as 50–999 copies/mL of plasma viral load with antiretroviral therapy (ART) for at least 6 months. HIV-1 DRM detection used validated in-house protocol.
Results
A total of 470 sequences were obtained, and 13 HIV-1 genotypes were identified, among which CRF08_BC (47.5%), CRF07_BC (22.3%) and CRF01_AE (10.0%) subtypes were the most prevalent. The overall prevalence of DRMs was 45.7% (215/470), and the prevalence of DRMs to non-nucleoside reverse transcriptase inhibitors (NNRTIs), nucleoside reverse transcriptase inhibitors (NRTIs) and protease inhibitors (PIs) was 39.4% (185/470), 20.6% (97/470) and 5.3% (25/470), respectively. The most common NNRTI-associated mutations were K103N (16.0%), E138A (6.6%), V179D (6.6%) and P225H (4.9%), and those in NRTIs were M184V (17.0%), D67N (3.4%) and K65R (3.0%). PI-associated mutations were infrequent, occurring in less than 1.8% of cases. The prevalence of NNRTI-associated mutations (K101E and Y188C) was found to be statistically significant among various LLV groups. Additionally, significant variations were observed in the prevalence of NNRTI-associated mutations (V106I, V106M, E138A and P225H), NRTI-associated mutation (K65R) and PI-associated mutations (L33F and Q58E) across different subtypes.
Conclusions
The prevalence of DRMs in ART-experienced patients with LLV was high, and HIV-1 genotypes exhibited diversity in Yunnan Province. These findings indicate that regular DRM monitoring during LLV episodes was essential for effective clinical treatment and management in this region.
Introduction
Antiretroviral therapy (ART) remains the preferred method for achieving plasma viral load (pVL) suppression in current people living with HIV (PLHIV), thereby reducing mortality,1 and preventing the likelihood of transmission.2 At the end of 2023, a significant number of PLHIV in China, estimated at 1.166 million out of 1.226 million, had been accessing ART.3 With unprecedented ART scale-up, HIV suppression rates (<1000 copies/mL) have also increased in China, rising from 88% in 20124,5 to 95.1% in 2023 (the 9th national academic conference on HIV/AIDS, China, 2024, unpublished data). Despite these beneficial efforts, 4.3% of PLHIV undergoing ART is occurring low-level viremia (LLV). Recently, multiple studies have shown that LLV increases the risk of virological failure,6–9 all-cause mortality,10 unprotected sex,11 poor immune reconstitution12 and non-AIDS events,13 which is a challenge for maintaining the effectiveness of ART.
The clinical importance and treatment of LLV are still being debated, with one contributing factor being the inadequacy of plasma HIV-RNA for efficient genome amplification, thereby complicating the process of standard HIV genotyping. Despite this increasing attention to LLV, clinical data from China are still rare and incomplete.14 Yunnan, located in Southwestern China, is the epitome of China’s current situation regarding HIV and is one of the most existing PLHIV in this country. In 2020, Yunnan was the first province to achieve the UNAIDS’s 90-90-90 targets in China and is now progressing towards the 95-95-95 goals. A high proportion of PLHIV have successfully achieved virological suppression, but 22.6% of patients had experienced LLV.8 Therefore, the management of LLV has become a formidable challenge to public health in this province.
HIV-1 drug resistance mutations (DRMs) are a cause and a consequence of the clinical failure of ART, as evidenced by more recent research findings.15,16 Therefore, the evaluation of DRMs is also crucial for guiding LLV clinical treatment. With improved treatment for HIV infection, it is crucial to monitor LLV tendency and drug-resistant prevalence of LLV. This study aimed to estimate the prevalence of DRMs among PLHIV with LLV in Yunnan Province, to provide policy-making support for clinical decisions in the region.
Methods
Study design and participants
This cross-sectional observational study was performed from January 2023 to December 2023 at the HIV Genotyping Laboratory, Yunnan Infectious Disease Hospital/Yunnan AIDS Care Center, which is the largest HIV/AIDS referral hospital in Southwestern China, manages the clinical treatment of over 130 000 PLHIV in the province. At the time of the study, there were approximately 110 000 PLHIV who regularly underwent pVL testing in the outpatient department. The primary inclusion criteria included the following: (i) ART for at least 24 weeks, (ii) currently receiving treatment for ART at the time of the enrolment, (iii) pVL levels between 50 and 999 copies/mL and (iv) HIV-1 pol sequences were successfully amplified. The suboptimal gene sequences and duplicate samples were excluded from participation in this study.
The National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention published the revised ‘National AIDS Free Antiviral Treatment Manual-Fifth Version’ in 2023. LLV was defined as a pVL range of 50 and 999 copies/mL after at least 24 weeks of ART initiation. Before that, DRM testing was only performed on PLHIV with pVL ≥ 1000 copies/mL; however, we chose a more stringent testing threshold of pVL ≥ 50 copies/mL.
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the research ethics committee of Yunnan Provincial Infectious Disease Hospital (no. KE2024002).
Sample preparation and viral load testing
Peripheral blood samples were collected in EDTA tubes (9 mL), followed by centrifugation to separate the plasma, and stored at −80°C until assayed. HIV viral load testing was conducted following reagent instruction. Samples with pVL ranging from 50 to 999 copies/mL underwent subsequent HIV drug resistance testing by reported method.17
HIV-1 genotyping analysis
HIV-1 sequences were conducted utilizing a previously validated in-house protocol with the complete genome (9719 bp) of HXB2 as the reference, that amplification of the PR region (codons 1–99) and partial RT region (at least codons 1–250) genes. The amplified sequences were spliced using CExpress software and corrected with BioEdit software. HIV genotyping was preliminarily determined by the online analysis tool HIV Databases BLAST (https://www.hiv.lanl.gov/content/sequence/BASIC_BLAST/basic_blast.html). The phylogenetic tree was constructed through the neighbor-joining method by MEGA software for confirmation. The reliability of the tree topology and branching order was evaluated by bootstrap analysis with 1000 replicates. All the reference sequences for major HIV-1 subtypes and circular recombinant forms (CRFs) were downloaded from the HIV Sequence Database (https://www.hiv.lanl.gov/content/sequence/HIV/mainpage.html). When the two evaluation results were inconsistent, the jpHMM tool was used to verify (http://jphmm.gobics.de/submission_hiv). Sequences that could not be identified as any known subtype or CRFs were defined as unique recombinant forms (URFs).
HIV-1 drug resistance analysis
The HIV-1 sequences in FASTA format were submitted to the Stanford HIVdb genotypic resistance database (https://hivdb.stanford.edu/hivdb/by-sequences/) to identify any DRMs. The degree of drug resistance to each antiretroviral drug was classified into five levels according to the Stanford HIV Genotypic Resistance Interpretation Algorithm: susceptible, potential low-level resistance, low-level resistance, intermediate resistance and high-level resistance. HIV drug resistance was defined as the occurrence of low-level or higher resistance to at least one antiretroviral drug; otherwise, it was defined as HIV drug sensitivity.
Statistical analysis
Categorical variables were presented as frequency and percentages, while continuous variables were summarized with median and IQR. Categorical variables were compared using the χ2 test or Fisher exact test. The P-value was two-sided, and an alpha level of 0.05 was used to define statistical significance. All analyses were conducted using GraphPad Prism (version 10.1.2) and R software (version R 4.2.2).
Results
Sequence amplification
Generally, 7635 PLHIV had received DRM testing, including 789 LLV and 6846 high-level viremias (HLV, ≥1000 copies/mL) cases during the observation period. The amplification success rates of PR/RT region sequences were 59.6% (470/789) in LLV and 87.2% (5970/6846) in HLV. There was a significant difference in amplification rates between LLV and HLV groups (P < 0.001). According to pLV levels, we divided the categories of LLV into five groups: 50–199, 200–399, 400–599, 600–799 and 800–999 copies/mL. The positive rate of amplification was increased significantly with pLV levels (χ2 test for trend, P < 0.001) (Table 1).
Table 1.
The amplification positive rates of different viremia categories
| pVL range (copies/mL) | No. of all samples | No. of positive samples | Positive rate (%) |
|---|---|---|---|
| 50–199 | 77 | 35 | 45.5 |
| 200–399 | 382 | 209 | 54.7 |
| 400–599 | 168 | 111 | 66.1 |
| 600–799 | 103 | 69 | 67.0 |
| 800–999 | 59 | 46 | 78.0 |
Characteristics of LLV individuals
The clinical characteristics of LLV individuals enrolled in this study are shown in Table 2. The median age was 46.3 years (IQR, 37.2–54.4 years) at the time of genotyping, and most patients were female (68.1%). The median time between initiation and LLV onset of antiviral treatment was 5.8 years (IQR, 2.6–9.6 years). The main ART regimen in LLV individuals was non-nucleoside reverse transcriptase inhibitor (NNRTI)-based (84.9%), followed by protease inhibitor (PI)-based (11.7%). Sixteen cases of integrase inhibitor (INSTI)-based were reported.
Table 2.
Demographic characteristics of the study participants
| Characteristic | LLV (N = 470) |
|---|---|
| Age, year, median (IQR) | 46.3 (37.2, 54.4) |
| Sex, n (%) | |
| Female | 320 (68.1) |
| Male | 150 (31.9) |
| ART history, year, median (IQR) | 5.8 (2.6, 9.6) |
| Marital status, n (%) | |
| Unmarried | 135 (28.7) |
| Married or cohabiting | 269 (57.2) |
| Divorced or widowed | 66 (14.1) |
| Transmission category, n (%) | |
| HSX | 299 (63.6) |
| MSM | 31 (6.6) |
| MTCT | 15 (3.2) |
| IDU | 65 (13.8) |
| Plasmapheresis | 2 (0.4) |
| Unknown | 58 (12.4) |
| ART regimens, n (%) | |
| NRTIs + NNRITs | 399 (84.9) |
| NRTIs + INSTIs | 16 (3.4) |
| NRTIs + PIs | 55 (11.7) |
| pVL at LLV, copies/mL, median (IQR) | 397 (264, 597) |
ART, antiretroviral therapy; HSX, heterosexual orientation; IDU, injection drug use; INSTIs, integrase strand transfer inhibitors; LLV, low-level viremia; MSM, men who have sex with men; MTCT, mother-to-child transmission; NNRTIs, non-nucleoside reverse transcriptase inhibitors; NRTIs, nucleoside reverse transcriptase inhibitors; PIs, protease inhibitors; pVL, plasma viral load.
Distribution of HIV-1 subtypes
A total of 13 HIV-1 subtypes/circulating recombinant forms (CRFs) were successfully identified. The predominant HIV-1 genotypes were CRF08_BC (47.5%), followed by CRF07_BC (22.3%) and CRF01_AE (10.0%). Additionally, 69 (14.7%) URFs were identified. The distributions of HIV-1 genotype are displayed in Table S1 (available as Supplementary data at JAC Online).
Prevalence of DRMs
Overall, the prevalence of DRMs was 45.7% (215/470) in LLV patients. The prevalence of DRMs to NNRTIs, NRTIs and PIs was 39.4%, 20.6% and 5.3%, respectively. NNRTI- and NRTI-associated DRM rates decreased in the LLV patients compared to those with HLV, while there was no difference in the prevalence of PI-associated DRMs [Figure 1(a)]. DRMs to both NNRTI/NRTI-associated were 16.6% (78/470), while simultaneous mutations to all three classes of antiviral drug were 2.1% (10/470).
Figure 1.
The percentage of NRTI, NNRTI and PI resistance mutations (a) and HIV-1 drug resistance mutation sites (b) and different-level resistance to antiretroviral drugs (c) in PLHIV. ABC, abacavir; ATV/r, atazanavir/ritonavir; AZT, zidovudine; DDI, didanosine; DOR, doravirine; DRV/r, darunavir/ritonavir; D4T, stavudine; EFV, efavirenz; ETR, etravirine; FPV/r, fosamprenavir; FTC, emtricitabine; HLV, high-level viremia; IDV/r, indinavir/ritonavir; LLV, low-level viremia; LPV/r, lopinavir/ritonavir; NFV, nelfinavir; NVP, nevirapine; RPV/r, rilpivirine/ritonavir; SQV/r, saquinavir/ritonavir; TDF, tenofovir disoproxil fumarate; TPV/r, tipranavir/ritonavir; 3TC, lamivudine. * indicates statistically significant differences (P < 0.05). NS indicates statistically not significant.
We identified many mutations in LLV patients (Figure 1b), including 30 types of mutations at 16 NNRTI-associated resistance sites, 26 types of mutations at 14 NRTI-associated resistance sites, 3 PI-associated major resistance mutation sites and 6 PI-associated accessory resistance mutation sites. The most common NNRTI-associated mutations were K103N (16.0%), E138A (6.6%), V179D (6.6%) and P225H (4.9%), and the top three NRTI-associated mutations were M184V (17.0%), D67N (3.4%) and K65R (3.0%). The prevalences of major mutation sites were lower in LLV patients compared with HLV patients.
The drug resistance levels for each antiviral drug in LLV patients are shown in Figure 1(c). High-level resistance to both NNRTIs and NRTIs was observed (14.9%), and three patients exhibited high-level resistance to simultaneously three-class drugs. In NNRTIs, the DRMs of EFV (33.6%) and NVP (33.6%) were the highest, and the rates of drug resistance observed for both agents were similar (26.2% versus 26.4%). Moreover, etravirine (16.8%) had a higher rate of potential low-level resistance. NRTIs yielded similar results, with the highest rates of drug resistance to FTC (18.9%) and 3TC (18.9%). All PIs showed very high drug sensitivity (>96%); no DRV/r resistant strains were identified.
Prevalence of DRMs stratified by HIV-1 RNA viral load
We analysed the discrepancy of DRMs in different levels of HIV-1 RNA viral load (Figure 2) and found that DRMs were present in each of the LLV groups. The DRM rates of pVL 50–199, 200–399, 400–599, 600–799 and 800–999 copies/mL among LLV individuals were 40.0%, 46.4%, 44.1%, 47.8% and 47.8%, respectively (P > 0.05). Of these, the frequency of NNRTI-associated (K103N, E138A and V179D) and NRTI-associated DRMs (D67N and M184 V) exceeded 2% in all LLV groups. No PI-associated DRMs were detected in the 50–199 copies/mL group. The prevalence of two NNRTI-associated mutations, K101E and Y188C, was statistically different in those LLV groups (P < 0.05).
Figure 2.
Prevalence of DRM sites with (a) NNRTIs, (b) NRTIs and (c) PIs stratified by LLV group. NNRTIs, non-nucleoside reverse transcriptase inhibitors; NRTIs, nucleoside reverse transcriptase inhibitors; PIs, protease inhibitors. * indicates statistically significant differences (P < 0.05).
Prevalence of DRMs stratified by HIV-1 genotypes
We analysed DRMs in three predominant epidemic HIV-1 subtypes (CRF08_BC, CRF07_BC and CRF01_AE), and the results showed marginal significance (Figure 3). CRF08_BC was the most common subtype carrying NNRTI-associated DRMs (48.9%) and was rare to develop PI-associated DRMs (2.7%). The cases of NNRTI-, NRTI- and PI-associated DRMs in the CRF08_BC subtype were 109, 48 and 6; in the CRF07_BC subtype, they were 32, 21 and 13; and in the CRF01_AE subtype, they were 13, 9 and 4, respectively. The prevalences of NNRTI-associated mutations (V106I, V106M, E138A and P225H), NRTI-associated mutations (K65R) and PI-associated mutations (L33F and Q58E) were significantly different across various subtypes (P < 0.05). Additionally, URFs also carried many DRMs (see Table S2). There was no significant difference in the prevalence of major DRM sites between URFs and the three subtypes.
Figure 3.
Differences in DRM sites with (a) NNRTIs, (b) NRTIs and (c) PIs by predominant HIV-1 genotypes. NNRTIs, non-nucleoside reverse transcriptase inhibitors; NRTIs, nucleoside reverse transcriptase inhibitors; PIs, protease inhibitors. * indicates statistically significant differences (P < 0.05).
Discussion
Our study aims to investigate the prevalence of DRMs among PLHIV with LLV in Southwestern China. Before this, HIV drug resistance testing was only recommended in patients with pVL ≥ 1000 copies/mL after at least 6 months of ART, as delineated by the criteria for ART failure. Limited information is available regarding the genotypic resistance of patients with LLV, potentially impeding timely treatment. In 2023, the Chinese health department updated the criteria for ART to include LLV (50–1000 copies/mL).18 Therefore, this study tested samples with pVL 50–999 copies/mL for resistance to inform the treatment strategies for patients with LLV. The results showed that the overall prevalence of DRMs was 45.7%, which was consistent with ART failure in Yunnan.19 The prevalence among LLV individuals was similar to that in other regions of China, such as 42.3% in Zhengzhou,20 40.5% in Jiangsu21 and 47.1% in Guangdong.22
The practical application of reported methods for HIV drug resistance is constrained by the suboptimal pVL levels in patients with LLV. Recently, there have been several advancements in amplification success rates through the utilization of ultracentrifugation and specific primers.9,14 As in previous studies,22 we used ultracentrifugation to concentrate HIV-RNA, and the overall amplification positive rate was 59.6%. It is apparent that as pVL increases, the amplification success rate increases.
PLHIV typically follows the two NRTI + NNRTI/PI/INSTI regimens as recommended in the guidelines. As with other studies,20–22 NNRTIs had the highest drug resistance rate compared to NRTIs and PIs. M184V (17.0%) and K103N (16.0%) were identified as the most frequently detected mutations in NNRTIs and NRTIs, respectively, which was different from the major NNRTI mutations V179 reported in Zhengzhou.20 In addition, in this study, E138A, V179D, P225H, D67N and K65R were also frequently detected (>3.0%). Consistent with the previous reports,16 the frequency of major NRTI- and NNRTI-associated DRMs was significantly lower in LLV patients compared to HLV patients. In addition, while the occurrences of D67G, S68N, T69D and E138G/K were slightly elevated in LLV patients, they were considered as low-level DRMs, which may contribute to the occurrences of LLV. M184V and K65R are associated with intermediate to high decreases in susceptibility to 3TC and FTC, while also increasing susceptibility to AZT, thus partially countering the impact of D67N on AZT resistance. Those results may lead to partial resistance of 3TC and FTC, as well as the high susceptibility of AZT. Similarly, K103N, V179D and P225H could reduce susceptibility to EFV and NVP, ultimately resulting in elevated levels of resistance. Furthermore, K103N + P225H synergistically reduces susceptibility to doravirine (DOR). Despite DOR susceptibility being over 85% in this study, DOR cross-resistance was found in 69.5% of patients who failed first-line ART in China.23 Therefore, DOR should not be recommended without prior genotypic resistance testing. PI-associated DRMs were found to be notably rare (<1.8%) compared to NNRTIs and NRTIs. These mutations displayed high sensitivity to all PIs (>96%), with DRV/r showing 100% susceptibility. A longitudinal study also found that LLV patients on PI-based regimens rarely developed new DRMs.24 Hence, PIs can be used as alternative drugs when patients exhibit persistent LLV, as ongoing viral replication in the setting of suboptimal ART may lead to the emergence of further DRMs.25,26
Multiple recent studies have demonstrated that elevated pLV may heighten the likelihood of subsequent VF in LLV patients,9,27,28 with VF potentially stemming from DRMs of LLV.29 This study showed no correlation between the prevalence of DRMs and pVL, which contradicts the previous reports.20 However, the prevalence of DRMs in all LLV groups was inconsistent, with significant differences found in NNRTI-associated K101E and Y188C. This could partly explain the differences in DRM site selectivity observed in LLV patients. Further studies with a larger sample size are needed to confirm the results.
We identified 13 HIV-1 genotypes in this study, which reflects the genetic diversity of HIV-1 in Yunnan. CRF08_BC, CRF07_BC and CRF01_AE are still the predominant strains in this region, consistent with several previous investigations.30–33 In addition to the known CRFs, URFs also have a greatly increased proportion in our study. In the past few years, the variety of new URFs has been increasing, which might be attributed to the complexity of the HIV-1 gene pool resulting from long-term epidemics. The consequence may be contributed to the emergence of novel CRFs, with CRF170_0107 having recently been identified in Yunnan.34
Overall, there was no significant difference in the prevalence of major DRMs among the three subtypes, except for certain mutations that exhibited subtype-specific patterns. E138A and P225H were mostly found in the CRF08_BC subtype; K65R, V106M and Q58E were mostly found in the CRF07_BC subtype; V106I and L33F were mostly found in the CRF01_AE subtype. In contrast, there were no differences in the frequency of V106I/M among pre-treatment HIV-1 subtypes32 and no differences in the frequency of E138A, P225H and L33F among ART failure HIV-1 subtypes.35 These results suggest that specific DRM sites may show diversity among various subtypes in LLV patients.
However, this study also has some limitations. First, limited by the amplification technology, the genetic sequences of all patients were not obtained. Second, the proportion of PLHIV with pVL of 50–199 copies/mL and 800–999 copies/mL was lower (<10%), potentially introducing selection bias into subsequent analyses. DRMs focused on NNRTIs, NRTIs and PIs, without considering INSTIs, which are being utilized by a growing number of PLHIV.
In summary, these findings indicate a high prevalence of DRMs among ART-experienced PLHIV with LLV in Yunnan Province, primarily characterized by resistance to NNRTIs and NRTIs. Certain DRMs exhibited significant variations in prevalence among different pVL ranges and HIV-1 subtypes. This study has shown that conducting HIV drug resistance testing at LLV is imperative, and its implementation contributes to identifying patients earlier who need to alter their ART regimens. Furthermore, currently, there is a lack of recommendations for the management of LLV patients in China’s current ART guidelines; these data will provide information for clinical decision-making and the update of guidelines.
Supplementary Material
Acknowledgements
We thank the Department of Laboratory Medicine at Yunnan Provincial Infectious Disease Hospital for their support of this work.
Contributor Information
Yuanlu Shu, School of Public Health, Kunming Medical University, Kunming 650500, China; Department of Laboratory Medicine, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Jiafa Liu, Department of Public Health, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Cuixian Yang, Department of Laboratory Medicine, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Jianjian Li, Department of Laboratory Medicine, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Mi Zhang, Department of Science and Education, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Yuan Li, School of Public Health, Kunming Medical University, Kunming 650500, China; Department of Laboratory Medicine, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Xuemei Deng, Department of Laboratory Medicine, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Xingqi Dong, Department of Laboratory Medicine, Yunnan Provincial Infectious Disease Hospital, Kunming 650301, China.
Funding
This work was supported by the Major Science and Technology Project of Yunnan Provincial Science and Technology Department (grant numbers 202102AA310005 and 202405AJ310002), Talents Project of Yunnan Provincial Science and Technology Department (grant number 202305AC160021), Reserve Talents Project of Yunnan Provincial Health Commission (grant number H-2019044), Joint Special Funds for the Department of Science and Technology of Yunnan Province-Kunming Medical University (grant number 202201AY070001-208) and Kunming Medical University AIDS co-infectious disease diagnosis and treatment technology innovation team (grant number CXTD202111).
Transparency declarations
None to declare.
Author contributions
J.Li, M.Z., C.Y. and X.Do designed the study. Y.L., X.De and J.Liu performed the experiments. Y.S. and J.Liu analysed the data and wrote the manuscript. Y.S., J.Liu, Y.L. and X.De participated in the data collection. All authors read and approved the final version of the manuscript.
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Supplementary data
Tables S1 and S2 are available as Supplementary data at JAC Online.
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.