The National Free Antiretroviral Therapy (ART) Program in China has initiated to provide ART to HIV-1 patients, which has acted as an efficient method to suppress viral replication and helps prevent onward transmissions. But the problems of HIV drug resistance (HIVDR) may also come along. There is little data on the prevalence of HIVDR in Chengdu, where the number of HIV/AIDS patients ranks first among provincial capitals. Therefore, epidemiological surveillance was conducted in this area. From 2014 to 2016, HIV/AIDS patients (15 years and older) who had received first-line ART for at least six months were enrolled. Demographic, behavioral information and medical history were recorded, and blood samples were collected for viral loads and immune cell count analyses. HIV-1
AIDS, also known as “acquired immunodeficiency syndrome,” is a highly infectious disease caused by human immunodeficiency virus (HIV). It has been widely spread around the world, with approximately 37.9 million people living with HIV worldwide at the end of 2018 [
Application of highly active antiretroviral therapy (HAART) has significantly reduced the transmission of HIV and has decreased HIV-related morbidity and mortality [
Previous investigations around the world have shown that the prevalence of HIVDR varies in different regions, during different time periods and in different target populations. WHO reported that the prevalence of any HIVDR among all individuals receiving treatment ranged from 3% to 29% [
Sichuan is a representative province in Southwest China and is adjacent to Yunnan and Tibet Autonomous Region. Chengdu is the capital city of Sichuan Province and acts as the political, economic, and cultural center of this area. National surveillance shows that HIV infection rates are incredibly high in Southwest China and increases in HIV epidemics among men who have sex with men (MSM) have been especially rapid in urban centers [
The first HIV-1 case in Chengdu was reported in 1992. By the end of 2016, a total of 18,603 people were living with HIV in Chengdu, which accounts for the largest HIV/AIDS population among other provincial capitals, and 15,633 patients were receiving ART. However, there were little data on the molecular epidemiology of HIV-1 and the prevalence of drug resistance-associated mutations (DRMs) in this area. Therefore, epidemiological surveillance was conducted in patients receiving ART treatment in Chengdu, to provide HIV-1 subtypes, the prevalence of DR, and DRM profiles and thus to optimize clinical management, prevention, and control of HIV.
This study was carried out at the Center for Disease Control and Prevention at Chengdu, Sichuan Province, West China. From 2014 to 2016, HIV/AIDS patients (15 years and older) who had received first-line ART for at least 6 months were enrolled in this study. The patients who were on second-line ART (<6 months) were excluded. Blood samples were collected in EDTA containers, and plasma was extracted and cryopreserved for analyses. Patients or their guardians (patients under 18 years old) who provided written informed consent participated in the study. Demographic, behavioral information and medical history were recorded using a standard questionnaire.
To assess immune response, CD4+ T cell count was measured by a flow cytometer BD FACSCount™ System (Becton Dickinson, Franklin Lakes, N.J., USA). HIV-1 RNA viral load (VL) was quantified with an Abbott RealTime HIV-1 Amplification Reagent Kit (Abbott Molecular, Chicago, USA) and NUCLISENS EASYQ HIV-1 2.0 (BioMérieux, France) according to the manufacturer’s instructions. Virologic failure was defined as measurement of VL above 1000 HIV RNA copies/ml, and then, HIV-1
HIV viral RNA was extracted from plasma using the Abbott RealTime HIV-1 Amplification Reagent Kit and then was reverse transcripted into cDNA by using the AccessQuick™ RT-PCR System (Promega, Madison, Wisconsin, USA). The
The obtained nucleotide sequences were assembled, edited, and aligned using ChromasProl.33 and BioEdit 7.0. HIV-1 subtyping was performed by constructing the HIV-1
Statistical analysis was performed using SPSS Statistics version 22.0. Categorical variables were described in numbers and proportions. Possible associations of HIV-1 subtypes, HIV-1 drug resistance with demographic, exposure category, and clinical variables were analyzed by using the Chi-square test or Fisher’s exact test and logistic regression. All tests were two-sided with statistical significance at
Between 2014 and 2016, a total of 13,872 HIV-infected patients were tested for HIV-1 VL. 4.7% (653/13872) of cases were considered treatment failure. A total of 481 (481/653) samples were amplified and sequenced successfully for subtypes and genetic resistance. Most of the subjects were male (411/481, 85.4%), and the main route of infection was heterosexual contact (342/481, 71.1%). The median age was 41 years (range: 15-81years), of which 50.3% were married. The demographic and subtype distributions of 481 patients are presented in Table
Demographic characteristics and HIV-1 subtypes of the study participants.
Participants | Subtypes | ||||||
---|---|---|---|---|---|---|---|
CRF01_AE | CRF07_BC | CRF08_BC | B | C | CRF55_01B | ||
Total | 481 | 261 | 200 | 9 | 6 | 3 | 2 |
Gender | |||||||
Male | 411 (85.4) | 222 (85.1) | 175 (87.5) | 4 (44.4) | 5 (83.3) | 3 (100.0) | 2 (100.0) |
Female | 70 (14.6) | 39 (14.9) | 25 (12.5) | 5 (55.6) | 1 (16.7) | 0 (0.0) | 0 (0.0) |
Age | |||||||
15~25 | 53 (11.0) | 22 (8.2) | 28 (14.0) | 1 (11.1) | 2 (33.3) | 0 (0.0) | 0 (0.0) |
26~40 | 179 (37.2) | 94 (36.0) | 75 (37.5) | 5 (55.6) | 2 (33.3) | 1 (33.3) | 2 (100.0) |
>40 | 249 (51.8) | 145 (55.6) | 97 (48.5) | 3 (33.3) | 2 (33.3) | 2 (66.7) | 0 (0.0) |
Marital status | |||||||
Married/cohabiting | 242 (50.3) | 138 (52.9) | 94 (38.8) | 5 (55.6) | 3 (50.0) | 2 (66.7) | 0 (0.0) |
Unmarried | 148 (30.8) | 79 (30.3) | 63 (42.6) | 1 (11.1) | 2 (33.3) | 1 (33.3) | 2 (100.0) |
Divorced/widowed/separated | 85 (17.7) | 40 (15.3) | 41 (48.2) | 3 (33.3) | 1 (16.7) | 0 (0.0) | 0 (0.0) |
Unknown | 6 (1.2) | 4 (1.5) | 2 (33.3) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
Infection routes | |||||||
Heterosexual contact | 342 (71.1) | 189 (72.4) | 138 (69.0) | 9 (100.0) | 4 (66.7) | 2 (66.7) | 0 (0.0) |
Homosexual contact | 98 (20.4) | 49 (18.8) | 45 (22.5) | 0 (0.0) | 2 (33.3) | 0 (0.0) | 2 (100.0) |
Blood transfusion | 1 (0.2) | 0 (0.0) | 1 (0.5) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
Intravenous drug injection | 7 (1.6) | 3 (1.1) | 4 (2.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
Unknown | 33 (6.9) | 20 (7.7) | 12 (6.0) | 0 (0.0) | 0 (0.0) | 1 (33.3) | 0 (0.0) |
According to the HIV Drug Resistance Database, 245 DR cases were identified in 481 sequences. The prevalence of DR from 2014 to 2016 was 1.8% (245/13872) in treatment-experienced patients and 37.5% (245/653) in virologic failure patients. The comparison of characteristics between patients with and without DR is listed in Table
Demographic characteristics of treatment-experienced HIV-1 individuals with virologic failure and univariate analyses for correlates of drug resistance.
Variables | Without DR | DR | |
---|---|---|---|
Gender | |||
Male | 202 (85.6) | 209 (85.3) | 0.94 |
Female | 34 (14.4) | 36 (14.7) | |
Age (years) | |||
15~ | 24 (10.2) | 21 (8.6) | 0.84 |
25~ | 63 (26.7) | 67 (27.3) | |
35~ | 47 (19.9) | 57 (23.3) | |
45~ | 33 (14.0) | 36 (14.7) | |
≥55 | 69 (29.2) | 64 (26.1) | |
Marital status | |||
Married/cohabiting | 114 (48.3) | 128 (52.2) | 0.70 |
Single | 74 (31.4) | 74 (30.2) | |
Divorced/widowed/separated | 44 (18.6) | 41 (16.7) | |
Unknown | 4 (1.7) | 2 (0.8) | |
Infection routes | |||
Heterosexual contact | 166 (70.3) | 176 (71.8) | 0.83 |
Homosexual contact | 51 (21.6) | 47 (19.2) | |
IDU | 4 (1.7) | 3 (1.2) | |
Unknown | 15 (6.4) | 19 (7.8) | |
CD4+ T cell count (cells/ | |||
≤200 | 78 (33.1) | 177 (72.2) | 0.00 |
>200 | 151 (64.0) | 65 (26.5) | |
Unknown | 7 (3.0) | 3 (1.2) | |
Treatment duration (year) | |||
0.5~ | 57 (24.2) | 75 (30.6) | 0.28 |
1~3 | 136 (57.6) | 128 (52.2) | |
≥3 | 43 (18.2) | 42 (17.1) | |
Treatment regimen | |||
AZT+3TC+EFV/NVP/others | 91 (38.6) | 64 (26.1) | 0.00 |
D4T+3TC+EFV/NVP/others | 26 (11.0) | 24 (9.8) | |
TDF+3TC+EFV/NVP/others | 116 (49.2) | 156 (63.7) | |
3TC+EFV+NVP | 3 (1.3) | 0 (0.0) | |
Unknown | 0 (0.00) | 1 (0.4) | |
Treatment change | |||
Yes | 8 (3.4) | 17 (6.9) | 0.07 |
No | 228 (96.6) | 228 (93.1) | |
Viral load (log10) | |||
3~ | 130 (55.1) | 111 (45.3) | 0.10 |
4~ | 77 (32.6) | 98 (40.0) | |
≥3 | 29 (12.3) | 36 (14.7) | |
Subtypes | |||
CRF01_AE | 94 (39.8) | 167 (68.2) | 0.00 |
CRF07_BC | 131 (55.5) | 69 (28.1) | |
CRF08_BC | 8 (3.4) | 1 (0.4) | |
CRF55_01B | 0 (0.0) | 2 (0.8) | |
B | 2 (0.8) | 4 (1.6) | |
C | 1 (0.4) | 2 (0.8) |
Univariate analyses were conducted to correlate demographic characteristics with drug resistance (Table
In total, 1.2% were resistant to nucleoside reverse transcriptase inhibitors (NRTIs), 1.7% to non-NRTIs (NNRTIs), and 0.14% to protease inhibitors (PIs). The NRTI-associated mutations were forecasted to be highly resistant to lamivudine (3TC, 67.8%, 146/245) and abacavir (ABC, 40.4%, 99/245), resistant to stavudine (D4T, 50.2%, 123/245) and tenofovir (TDF, 47.76%, 117/245), and intermediate or low resistant to azidothymidine (AZT, 7.3%, 18/245). 96.33% of the patients were predicted to have high resistance to efavirenz (EFV) and nevirapine (NVP), followed by resistance to rilpivirine (RPV, 67.0%, 169/245) and etravirine (ETR, 67.3%, 165/245) (Figure
The categories of antiretroviral drugs and their susceptibility of resistance level. Numbers of patients with DR by NRTIs and NNRTIs (a), PIs (b) and their susceptibility of resistance level. H: high resistance, M: moderate resistance, L/P: low or potential resistance.
The prevalence of all DRMs to NRTIs, NNRTIs, and PIs was displayed in Supplementary Table
14 NRTI-associated DRMs were all found in CRF01_AE, and V75I/L/M, T69N/D, and L210W were not found in CRF07_BC (S Table
Since the 1980s, pioneers have focused on the issues of HIVDR [
Chengdu is an area with predominance of CRF01_AE and CRF08_BC, indicating distinct heterogeneity compared to what has been shown in other regions [
In addition, novel CRF such as CRF55_01B was first discovered in Chengdu, and both cases were MSM. CRF55_01B, a recombinant form of CRF01_AE and subtype B, was first identified in 2012 among MSM in China, becoming the third CRF in China [
The overall prevalence of DR in treatment-experienced patients was 1.8% in Chengdu from 2014 to 2016, which was relatively lower than that in other areas of China, such as Jiangsu, similar to that in Yunnan and also lower than the average rate of Sichuan [
CD4+ T cell count, CRF01 AE subtypes, and treatment with “TDF+3TC+EFV/NVP/other” are associated with DR. No significant differences were seen in other characteristics. Previous studies have suggested that patients with initial CD4+ T cell
The Chengdu ART regimen includes 3TC, one NRTI (AZT/D4T/TDF), and one NNRTI (EFV/NVP). The resistance to NRTIs was DDI (69.80%), 3TC (69.39%), FTC (69.39%), ABC (69.39%), D4T (50.20%), TDF (47.76%), and AZT (13.47%) based on the number of the cases. Although FTC and DDI were not used in clinical settings, significant cross-resistance was observed. The structure, mechanism, and efficacy of FTC are similar to 3TC, and FTC was predicted to have the same DR profiles with 3TC. Similar findings were seen for DDI with ABC. Under the 3TC-based medication regimen, a high proportion of drug resistance was observed for 3TC, most of which showed high and intermediate resistance. Besides, the number of cases resistant to AZT was the lowest, most of which showed low or potential resistance. Thus, 3TC+AZT is the best choice in the current NRTI regimen.
In our study, M184I/V (59.59%) was the most prevalent mutation associated with NRTI resistance in our study and was also frequently found in Europe, Africa, and other regions in China [
Patients infected with the CRF01_AE are associated with DR. All 14 NRTI-associated mutations and 16 NNRTI-associated mutations were all found in CRF01_AE. Both cases identified with CRF55_01B showed DR, suggesting that this newly discovered CRF may likely develop DRMs. NRTI-associated DRMs M184I/V and K65R and NNRTI-associated DRMs with extensively drug resistance K101E/H/P, V179I/D/E/T, Y181C/V, and G190A/E/K/Q/S/V were detected in CRF55_01B. PI-associated mutations were found in 97 cases, most of which were secondary mutations like L10I/V, A71I/T/V, and K20I/R, so, there were relatively few cases of DR. In this study, among the PI-associated DR mutations detected, K20I/R and T74S were mainly found in CRF01_AE while A71I/T/V, Q58E, and V82I were frequently observed in CRF07_BC, indicating that the presence of different mutations may vary among different subtypes.
There are some limitations in this study. Part of the cases did not obtain available genotypes, and hence, sensitive methods may need to be explored to improve genotyping success rate. We observed that several factors are associated with HIVDR and then large sample size will be required to ensure the accuracy of this conclusion. In order to better apprehend and evaluate the prevalence of acquired HIVDR in this area, attention should be devoted to the prevalence of drug resistance in ART-naïve HIV-1 infected patients.
In this study, the HIV-1 genetic diversity and frequency of DRMs varies among individuals with ART failure in Chengdu. The overall prevalence of DR remained low in the studied population. Surveillance of VL and DR in patients receiving ART is of great significance, which can adjust treatment regimens and improve the quality of life. It also plays a considerable role to develop a clinical strategy for the prevention of the transmission of drug-resistant strains of HIV in this area.
Acquired immunodeficiency syndrome
Human immunodeficiency virus
World Health Organization
Circulating recombinant forms
Virus load
Nucleoside reverse transcriptase inhibitors
Nonnucleoside reverse transcriptase inhibitors
Protease inhibitors
Lamivudine
Abacavir
Zidovudine
Stavudine
Tenofovir
Didanosine
Emtricitabine
Efavirenz
Nevirapine
Etravirine
Rilpivirine
Lopinavir
Atazanavir
Darunavir
Fosamprenavir
Indinavir
Nelfinavir
Saquinavir
Tipranavir.
All data generated or analyzed during this study are included in this article. All data and materials are presented in methods and results sections as shown in figures and tables. The data sets generated and/or analyzed during the current study are not publicly available due to policy of this project.
The authors report no conflict of interest connected with this study.
PXF, CJY, and LY designed the research; CJY, LY, LSJ, YD, SL, YL, GDH, and GYS performed the research and acquired data; CJY, LY, and YD analyzed the data; CJY, LY, LSJ, and YD wrote the paper; PXF and BS revised the manuscript; PXF approved the final version to be published. All authors read and approved the final manuscript. Chen Jiayi and Liu Yang contributed equally to this work.
We are grateful to the participants for their dedication and contribution to the research. We thank the support from the Public Health and Preventive Medicine Provincial Experiment Teaching Center at Sichuan University and the Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province. This study was supported by the National Mega Projects of Science and Technology in 13th Five-Year Plan of China: Technical Platform for Communicable Disease Surveillance Project (2017ZX10103010–002).
S Table 1: prevalence of DRMs in HIV-1 individuals with virologic failure in Chengdu from 2014 to 2016. S Table 2: distribution of HIV-1 DRMs in CRF01_AE and CRF07_BC.