Drug resistance mutations among people living with HIV with treatment failure in Henan Province, China

To the Editor: Drug resistance mutations (DRMs) involving human deficiency virus type 1 (HIV-1) diminish the efficacy of current antiretroviral therapy (ART) regimens, resulting in treatment failure. A better understanding of the prevalence of local DRMs that lead to ART failure can provide valuable data for clinical- and government-level decision-making. The DRM status of people living with HIV (PLWH) refractory to ART (viral load >200 copies/mL) was assessed based on analysis of plasma samples derived from PLWH in the Sixth People's Hospital of Zhengzhou from June 2018 to April 2022. Further, the partial polymerase (pol) and complete integrase gene-coding sequences were amplified, sequenced, and analyzed to identify DRMs. This study was approved by the Institutional Ethics Committee of the Sixth People's Hospital of Zhengzhou (No. 2019-04). All participants signed written informed consent before sample collection. Demographic data and medical records, including HIV viral load, CD4+ T-cell count, and transmission route, were collected. Genotypic drug resistance testing was performed as described previously.[1,2] DRMs and antiretroviral susceptibility were analyzed by submitting the identified sequences to the Stanford HIV-1 drug resistance database (http://hivdb.stanford.edu/), which is updated periodically. Subtypes of HIV isolates were analyzed using the REGA HIV-1 Subtyping Tool (http://dbpartners.stanford.edu:8080/RegaSubtyping/stanford-hiv/typingtool/) based on the partial pol region, which was further validated via phylogenetic analysis. A phylogenetic tree was constructed using Molecular Evolutionary Genetic Analysis (MEGA) software (version X) based on the maximum likelihood method and general time reversible model with 1000 bootstrap replicates. Statistical analysis was carried out using SPSS (version 25.0; Chicago, IL, USA). The measurement data of normal distribution were expressed as mean ± standard deviation. Independent-samples t-test was used for group comparison. The skew distribution data were expressed as median (interquartile range [IQR]), and the Wilcoxon test for independent samples was used for comparison between groups. Categorical variables were expressed as numbers or percentages. Chi-squared test was used for comparison between groups, and univariate logistic regression was used for analysis of risk factors. All statistical tests were bilateral, and P <0.05 indicated statistically significant differences. The analysis included a total of 921 HIV-1 patients, with a median age of 43 (IQR, 30–53) years. Male patients constituted 73.9% (681/921) of the study population. Han ethnicity accounted for 99.5% (916/921) of the total patients. Further, 58.1% (535/921) of the patients were married and 41.9% (386/921) were single. Farmers accounted for 44.4% (409/921) of the total patients, followed by workers (36.9%, 340/921), non-workers (16.2%, 149/921), and students (2.5%, 23/921). Transmission route data were available for 921 patients, including those who underwent plasmapheresis constituting 32.5% (299/921), followed by those with heterosexual orientation (30.2%, 278/921), men who have sex with men (MSM) (22.6%, 208/921), mother-to-child transmission (10.5%, 97/921), and other or unknown data (4.2%, 39/921). Baseline CD4+ T-cell count data were available for 894 patients; the median CD4+ T-cell count was 81.5 cells/μL (IQR, 23.0–207.3). Baseline HIV-1 viral load (VL) data were available for 858 patients; the median baseline VL was 18,698.5 (min/max, 202.0–39,771,796.0) copies/μL. Detailed demographic data of the patients are listed in Supplementary Table 1, https://links.lww.com/CM9/B763. A total of 1078 patients who failed in ART treatment, the partial pol gene sequence was successfully amplified in 921, and the integrase (INT) gene sequence in 751 patients. The partial pol gene sequences were also successfully amplified in all the patients whose INT genes were sequenced. The prevalence of each subtype was as follows: B (59.5%, 548/921), CRF01_AE (23.7%, 218/921), CRF07_BC (10.0%, 92/921), CRF55_01B (5.3%, 49/921), CRF08_BC (1.0%, 9/921), C (0.3%, 3/921), CRF68_01B (0.01%, 1/921), and G (0.01%, 1/921) [Supplementary Table 2, https://links.lww.com/CM9/B763]. Based on the inferred phylogenetic tree [Supplementary Figure 1, https://links.lww.com/CM9/B763], all the determined subtypes clustered with reference strains, indicating consistent results and correct subtyping. Among the 921 patients, 748 patients (81.2%) had one or more DRMs for any drug class. When analyzed by individual drug class, the incidence of DRMs was 71.1% (655/921), 78.3% (721/921), 5.2% (48/921), and 3.1% (23/751) for nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), and integrase strand transfer inhibitors (INSTIs), respectively. The most common DRMs included M184V/I (576, 62.5%) for NRTIs, K103N/R (294, 31.9%) for NNRTIs, I54V (35, 3.8%) for PIs, and E157Q (25, 3.3%) for INSTIs [Supplementary Table 3, https://links.lww.com/CM9/B763]. For individual drugs, the most frequent high-level, medium-level, low-level, and potential low-level resistant drug were NVP, ETR, ABC, and ETR, respectively. Based on genotypes, DRMs mostly involved are CRF55_01B (91.8%, 35/49) and CRF01_AE (89.4%, 195/218), followed by B (79.2%, 434/548), CRF07_BC (71.7%, 66/94), and others/recombinants (57.1%, 8/14). A significant difference was found in the incidence of DRMs among different subtypes (P <0.05; Supplementary Table 2, https://links.lww.com/CM9/B763). Details of DRMs involving resistance to first- and second-line treatment regimens are presented in Figure 1.Figure 1: Predicted resistance to antiretroviral drugs among HIV-1 nucleotide sequences in treatment experienced patients with drug-resistance-associated mutation: Henan, 2018–2022. Resistance was predicted by Stanford HIV-1 drug resistance database. ABC: Abacavir; ATV/r: Atazanavir/r; BIC: Bictegravir; D4T: Stavudine; DTG: Dolutegravir; EFV: Efavirenz; FPV/r: Fosamprenavir/r; FTC: Emtricitabine; HIV-1: Human deficiency virus type 1; LPV/r: Lopinavir/r; NVP: Nevirapine; RAL: Raltegravir; SQV/r: Saquinavir/r; TDF: Tenofovir.The incidence of drug resistance was higher in males than females (P <0.05). When analyzed by age group, the incidence of DRMs was similar in the following age groups: 20–29 years, 30–39 years, 40–49 years, and 50–59 years. However, the incidence was lower in those aged 60 years or older as well as those younger than 20 years. Based on ART duration, the incidence of drug resistance tended to decrease with the extension of treatment time, from 92.5% (<1 year, 86/93) to 79.2% (≥5 years, 259/453), suggesting that short ART duration might be a risk factor for DRMs, but there was no significant difference (P >0.05). The incidence of DRMs in ART regimens containing NNRTI, PI, and integrase inhibitor (INI) was 87.7% (582/664), 63.8% (125/196), and 71.0% (22/31), respectively [Supplementary Table 4, https://links.lww.com/CM9/B763]. Generally, a delay of few weeks to months existed between blood sampling for viral load determination and genotypic drug resistance analysis. Therefore, PLWH with poor adherence might have restarted their treatment regimens, which could have subsequently suppressed viremia and thus failure to genotypic drug resistance due to low viral load. The pol gene was successfully amplified in 921 out of 1078 patients, and the INT gene was analyzed in 751 patients. INSTIs were not freely available to patients and were not covered by medical insurance in most provinces of China before 2022, so only a limited number of patients were treated with INSTIs and resistance testing against INSTIs was deemed unnecessary in clinical settings. Phylogenetic analysis based on the determined partial pol gene sequences indicated that the most common subtype was B, which accounted for 59.5%, followed by CRF01_AE, CRF07_BC, CRF55_01B, and CRF08_BC, which is consistent with subtype patterns in other regions[3,4] and our previous study.[1] Our data showed that the incidence of DRMs was 81.2% (748/921), which is consistent with the incidence worldwide (47–90%); however, it was significantly higher than that of 52–57% reported previously in China.[5] This might be explained by historical reasons as Henan province harbored the earliest group of PLWH due to illicit blood donation. When categorized by drug classes, the incidence of DRMs was 71.1% (655/921), 78.3% (721/921), 5.2% (48/921), and 3.1% (23/921) for NRTIs, NNRTIs, PIs, and INSTIs, respectively, which is consistent with the data reported previously.[5,6] In this survey, we found that the incidence of DRMs was the highest in patients with NNRTI-based regimens (582/664, 87.7%), followed by PI (125/196, 63.8%) and INSTI (22/31, 71.0%)-based regimens, which is consistent with previously reported incidence (50–97%) of DRMs to NNRTIs in patients who failed ART involving NNRTI-based regimens.[5,6] The higher incidence of DRMs against NNRTIs might be attributed to their lower resistance barrier and the frequent use as a first-line therapy. We further divided the patients into three groups according to the duration of ART. Although no significant differences (P >0.05) were found, the incidence of DRMs was the highest in patients with an ART duration of less than one year (86/93, 92.5%), followed by 1–5 years (276/355, 82.4%) and more than 5 years (359/453, 79.2%). Further studies are needed to determine the cause of this phenomenon. The incidence of DRMs against lamivudine (3TC) was 63.4%. However, Dovato, a combination of 3TC/dolutegravir (DTG) in a single tablet, showed comparable efficacy in suppressing viremia even in the presence of DRMs against 3TC, possibly due to the high efficacy of DTG.[6] The incidence of DRMs in patients treated with PI-based regimens was 63.8%, which is significantly lower than in NRTI- and NNRTI-based regimens, possibly due to its high resistance barriers and efficacy. In case of INSTIs, all levels (high/mid/low) of resistance were observed for drugs (BIC, Cabotegravir (CAB), DTG, EVG, and RAL) while resistance against EVG and RAL, the most widely used, was the most common. PLWH showing medium- or high-level resistance to BIC, CAB or DTG were rare and generally associated with extensive resistance to all classes of drugs. In this study, we also observed a proportion of PLWH with viremia but undetectable DRMs. Further investigations indicated that almost all of them showed poor adherence to treatment. In addition, PLWH with a viral load >200 copies/mL was selected in this study, and only 85% was successfully amplified. We will determine the prescribed drug levels in plasma samples and optimize the genotypic drug resistance testing method to address this question in future studies. In summary, the incidence of DRMs is high for commonly used NRTIs and NNRTIs and is low for commonly prescribed PIs and INSTIs in Henan Province. Poor adherence to ART is a key challenge, which may have contributed substantially to the high incidence of DRMs in patients undergoing ART and elevate the risk in PLWH with viremia but no detectable DRMs. Education regarding adherence to regimens is essential to improve therapeutic efficacy and prevent the emergence of DRMs. Acknowledgements We would like to thank all the doctors, nurses, and patients who participated in this study. Funding This study was supported by grants from the Science and Technology Research Project of Henan Province (Nos. SB201903031 and 232102310203). Conflicts of interest None.

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