ABSTRACT.
India has the third-largest number of people living with HIV (PLHIV) in the world. A national program provides free access to standard uniform antiretroviral therapy. However, the program is not monitored by comprehensive drug resistance surveys. The aim of this study was to determine the prevalence of HIV drug resistance mutations (DRMs) among treatment-naive PLHIV in a large antiretroviral treatment center of the national program. This cross-sectional study was done in 2017 and involved 200 consecutive treatment-naive PLHIV. A target fragment of 1,306 bp in the reverse transcriptase and protease regions was amplified. Identification of mutations and drug resistance interpretation was done by HIV Genotypic Resistance Interpretation and International Antiviral Society-USA list. Sequencing was successful in 177 samples. The majority (98.8%; 175/177) belonged to subtype C. Nineteen of 177 patients (10.7%; 95% CI: 6.2%–15.3%) had at least one major DRM. The prevalence of non-nucleoside reverse transcriptase inhibitor (NNRTI) mutations was 10.2% (18/177). The most frequent mutations were E138A/K, A98G, K103N, V179D, and K101H/E. The prevalence of nucleoside reverse transcriptase inhibitor (NRTI) mutations was 1.1% (2/177). None of the samples had major protease inhibitor resistance mutations. The prevalence of NNRTI mutations in this study was >10%, crossing the threshold recommended by the WHO to change the NNRTI-based first-line regimen to non–NNRTI based. In 2021, the national program replaced efavirenz with dolutegravir in the first-line regimen of tenofovir, lamivudine, and efavirenz. As the majority (64%) of PLHIV in India are accessing free ART from the national program, this study highlights the need for regular nationally representative drug resistance surveys for optimizing antiretroviral regimens in the program.
INTRODUCTION
The target of the United Nations program on HIV/AIDS (UNAIDS) is to end the AIDS epidemic as a public health threat by 2030 by achieving its 95-95-95 goals. The 95-95-95 milestones are as follows: 1) 95% of estimated people living with HIV (PLHIV) should know their HIV status; 2) 95% of all individuals with an HIV diagnosis should be on antiretroviral treatment (ART); and 3) 95% of all patients on treatment should have a suppressed viral load. The UNAIDS data of 2023 show that 29.8 million of the 39 million PLHIV globally are receiving ART and 71% have a suppressed viral load.1 The third goal of having 95% virological suppression depends on providing effective regimens, which in turn is affected by prevailing drug resistance mutations (DRMs) among the affected population. The emergence and development of DRMs in treatment-naive people can jeopardize the efficacy of ART and lead to incomplete suppression of viral load, increased mortality, and higher rates of transmission in this population.2 Transmitted drug resistance (TDR) is a term used to describe resistance to at least one antiretroviral (ARV) drug in people who have never taken treatment before. It is thought to be the result of resistant strains being transmitted directly from previously treated persons.3 Furthermore, failure to respond to ART because of drug-resistant viruses increases the risk of morbidity and mortality in patients with HIV, specifically in countries where the number of ART options are limited.4
Transmitted drug resistance prevalence varies widely; in the United States and Europe, it ranges between 5% and 15%.5–10 With increasing numbers of PLHIV on treatment, TDR is also becoming a major health issue in resource-limited countries.10,11 Studies have also shown that patients who commenced their first-line ART regimen after receiving baseline HIV genotypic testing experienced greater HIV viral suppression than those who did not get baseline HIV genotypic testing.12,13 The Global Action Plan on HIV drug resistance 2017–2021, a multi-stakeholder plan coordinated and published by the WHO, encourages countries to monitor resistance and advises persons starting ARVs to test for pretreatment drug resistance (PDR). The WHO-recommended HIV drug resistance surveys were implemented in 56 countries between 2014 and 2021. These data show that more countries are approaching 10% PDR to non-nucleoside reverse transcriptase inhibitors (NNRTIs). When PDR to NNRTIs such as nevirapine and efavirenz approaches 10% in a nation, the WHO recommends switching to a non–NNRTI-based regimen.14
According to a recent annual report, the National AIDS Control Program of India provides free ART to 1.55 million PLHIV.15 There is no provision for routine drug resistance testing or for modifying individual regimens based on genotyping studies in the program. Therefore, prevalence studies are valuable in generating trends on HIV subtypes and DRM patterns in the country. Moreover, there are minimal data on the PDR of non–subtype B HIV strains, and as subtype C is predominant in India, pretreatment studies are deemed necessary in this region.16 According to a recent WHO report, a DRM survey was done in only 14 low-/middle-income nations, with very few representations in Southeast Asia.17 Despite the large number of PLHIV accessing treatment through the program, there is lack of data on potential drug resistance in treatment-naive patients in the program. This study sheds light on the extent of preexisting drug resistance among treatment-naive PLHIV and provides guidance for potential treatment options in the national program.
MATERIALS AND METHODS
Study population.
This study was conducted on 200 consecutive individuals newly diagnosed as being HIV-positive and ART-naive at the ART center of Banaras Hindu University (BHU) in 2017.
At the time of the study, the ART center at BHU had 19,744 PLHIV registered, with 6,000 patients alive and on ART. Inclusion criteria were all individuals attending the ART center, Sir Sundar Lal Hospital, BHU, Varanasi, who were newly diagnosed with HIV and were older than 18 years and who consented to the study. Exclusion criteria were individuals who were under the age of 18 years and who did not give consent. The study was approved by an institutional ethics committee (No. Dean/2015-16/EC/413). Demographic and clinical details were recorded from each patient’s white card, which was available at the ART clinic.
Sample collection and processing.
Whole blood of patients was collected into ethylenediamine tetraacetic acid tubes and used for CD4 estimation; in parallel, plasma was separated after centrifugation at 2,000 rpm at 4°C for 10 minutes and stored at −80°C until viral RNA isolation. The CD4 T-cell counts for all patients were performed using the BD FACS Count system (Becton, Dickinson, Franklin Lakes, NJ).
Nucleic acid extraction.
The HIV RNA was extracted manually using a QIAamp® Viral RNA mini kit according to the manufacturer’s instructions (Qiagen, Hilden, Germany; Cat. No. 52906). Viral RNA was stored at −80°C until use.
Reverse transcription polymerase chain reaction and nested polymerase chain reaction.
Amplification of complete protease (PR; codons 1–99) and partial reverse transcriptase (RT; codons 1–256) regions of the pol gene was performed by a previously published method.18,19 Synthesis of complementary DNA and polymerase chain reaction (PCR) were performed using the Thermoscript RT PCR System (Invitrogen, Carlsbad, CA; Cat. No. 1146016) with Platinum Taq DNA polymerase (Invitrogen; Cat. No. 10966018).
Sanger sequencing.
Sequencing was done by third-party commercial (Agri genome). Sequencing was done by using BigDye terminator V3.1 chemistry, and the instrument used was the Applied Biosystems (Foster City, CA) 37370xl DNA analyzer. Samples were proceeded after gel purification using the SureExtract PCR cleanup kit (Genetix Biotech Asia Pvt. Ltd., New Delhi, India).
Genotypic drug resistance testing and subtyping.
After sequencing, we used Recall software to build a contig using https://recall.bccfe.ca/ analysis, and the drug resistance pattern was determined by Stanford University HIV Genotypic Resistance Interpretation Algorithm v. 9.0 (https://hivdb.stanford.edu/hivdb/by-mutations/) and International Antiviral Society- USA (IAS-USA) mutation list 2022. The HIV-1 subtyping was performed on all of the samples in accordance with the recommendations of the REGA HIV-1 subtyping tool v. 3.0 (http://dbpartners.stanford.edu:8080/RegaSubtyping/stanford-hiv/typingtool/). We also assessed the mutation with the Stanford genotypic resistance calibrated population resistance (CPR) tool v. 8.0 interpretation algorithm (https://hivdb.stanford.edu/cpr/form/PRRT/).
STATISTICAL ANALYSES
Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS v. 23.0, IBM Corp., Armonk, NY). Simple descriptive statistics were used: mean ± SD for quantitative variables and frequency with percentage distribution for categorized variables.
RESULTS
Sociodemographic features of the study population.
Of the 200 patients recruited in the study, successful amplification and sequencing were done in 177 patients and are included in the study. Baseline characteristics of the patients are given in Table 1. Median age was 36 ± 10.05 years, and mean CD4 count was 233.1 cells/µL. All patients were started on first-line treatment with tenofovir + lamivudine + efavirenz. At the end of February 2022 (5 years from the collection of samples), 112 patients were alive and on ART (37 at our ART center, and 75 in other ART centers), 40 had died, 21 were lost to follow-up, and 4 patients had opted out of treatment.
Table 1.
Baseline sociodemographic characteristics of the study population
| Characteristics | Frequency (N = 177) | Percentage |
|---|---|---|
| Age (years) | ||
| < 30 | 38 | 21.47 |
| 30–39 | 58 | 32.77 |
| 40+ | 81 | 45.76 |
| Median ± SD | 36 ± 10.05 | – |
| Sex | ||
| Male | 107 | 60.45 |
| Female | 69 | 38.98 |
| Transgender | 1 | 0.56 |
| Sex ratio (male-to-female) | 1.55:1 | – |
| Education | ||
| Illiterate | 54 | 30.51 |
| Primary school | 32 | 18.08 |
| Secondary school | 68 | 38.42 |
| College and above | 23 | 12.99 |
| Marital status | ||
| Married | 129 | 72.88 |
| Unmarried | 27 | 15.25 |
| Widowed | 21 | 11.86 |
| Risk factor | ||
| Heterosexual | 102 | 57.63 |
| Blood transfusion | 5 | 2.82 |
| IDU | 5 | 2.82 |
| Migrant and trucker | 16 | 9.04 |
| Unknown | 49 | 27.68 |
| CD4 count (per µL) | ||
| < 200 | 97 | 54.80 |
| 200–349 | 34 | 19.77 |
| 350–499 | 22 | 12.43 |
| 500+ | 24 | 14.12 |
| WHO clinical stage | ||
| I | 99 | 55.93 |
| II | 23 | 12.99 |
| III | 28 | 15.82 |
| IV | 27 | 15.25 |
| Tuberculosis | ||
| Present | 43 | 24.29 |
| Absent | 134 | 75.71 |
IDU = injection drug use.
HIV subtyping and transmitted DRMs analysis.
A total of 177 HIV-1 pol gene sequences were amplified (1–99 amino acid positions) and up to amino acid position 256 for RT. Among the primary sequences, HIV-1 subtype C had the highest prevalence with 98.8% (175/177), followed by subtype A (0.56%, 1/177) and recombinant strain C, A1 (0.56%, 1/177), according to the REGA HIV-1 subtyping tool v. 3.0. According to the Stanford HIV Resistance Database v. 9 algorithm and IAS-USA mutation list, 10.73% (19/177) samples had at least one major PDR mutation. Eighteen of 177 samples had resistance against NNRTI, whereas two had nucleoside reverse transcriptase inhibitor (NRTI) resistance mutations. Among these 19 patients, eight patients expired within a year of starting therapy, one patient opted out of therapy, one patient was lost to follow-up (LFU), and nine patients are still alive and on treatment. One patient with DRMs for both NRTI and NNRTI regions (Y181C, D67N, K70R, K219E, and Q58E) is still alive and currently on a TLD (tenofovir, lamivudine, and dolutegravir) regimen (Table 2). We also assessed DRMs in our populations with the CPR tool, and the prevalence was 3.4% (6/177) (Table 2).
Table 2.
Drug resistance mutations with level of resistance against different antiretroviral drugs and outcome at 5 years
| ID | Age (Years)/Sex | Mutations | Drug Resistance | Current Status | Current Viral Load | Current Regimen | |
|---|---|---|---|---|---|---|---|
| NNRTIs | NRTIs | ||||||
| 21852 | 28/M | K103N*†‡ | EFV, NVP | – | Died | – | – |
| 21861 | 30/F | E138A*† | ETR,§ RPV,§ | – | Died | – | – |
| 21877 | 50/M | K103N*†‡ G190A*†‡ |
EFV, NVP, ETR,§ RPV§ | – | Died | – | – |
| 21887 | 26/M | M184LV*† | – | ABC,§ FTC, 3TC |
Died | – | – |
| 21904 | 33/F | A98G*† | NVP,‖ DOR,§ EFV,§ ETR,§ RPV,§ | – | – | – | |
| 21921 | 40/M | E138K*† | DOR,§ EFV,§ ETR,§ NVP,§ RPV‖ | – | Alive/TR-OUT | Not done | TLD |
| 21922 | 30/M | V179D*† | EFV,§ NVP,§ ETR,§ RPV§ | – | Alive/TR-OUT | TND | TLD |
| 21925 | 28/F | Y181C*†‡ D67N*†‡ K70R*†‡ |
DOR,§ EFV,‖ ETR,‖ NVP, RPV‖ |
ABC,‖ AZT, FTC§ |
Alive | TND | TLD |
| T215I*‡ K219E*†‡ |
– | 3TC,§ TDF‖ | – | – | |||
| 21946 | 40/F | L100I*† | DOR,§
EFV, ETR,‖ NVP, RPV |
– | Alive | TND | TLD |
| 21955 | 20/F | V108I*† | DOR,§ EFV,§ NVP,§ | – | Died | – | – |
| 21965 | 30/F | V179D*† | EFV,§ NVP,§ ETR,§ RPV§ | – | Alive/TR-OUT | Not done | TLD |
| 21972 | 30/M | L234I*† | DOR‖ | – | Died | – | – |
| 21996 | 25/F | K101H*† | EFV,§ NVP,§ ETR,§ RPV§ | – | Alive/TR-OUT | TND | TLD |
| 22007 | 26/M | E138A*† | ETR,§ RPV§ | – | Opted out | – | – |
| 22015 | 25/M | A98G*† | DOR,§ EFV,§ ETR,§ NVP,‖ RPV§ | – | Alive/TR-OUT | Not done | TLD |
| 22040 | 30/M | A98G*† | DOR,‖ EFV, ETR‖ | – | Died | – | – |
| K101E*†‡ | NVP, RPV | ||||||
| K103N*†‡ | – | ||||||
| E138A*† | – | ||||||
| 22045 | 53/M | K101E*†‡ | DOR,§ EFV,§ ETR,§ NVP,‖ RPV‖ | – | Died | – | – |
| 22063 | 32/M | V179D*† | EFV,§ NVP,§ ETR,§ RPV§ | – | Alive/TR-OUT | Not done | TLD |
| 22066 | 35/M | E138A*† | ETR,§ RPV§ | Alive | TND | TLD | |
ABC = abacavir; AZT = zidovudin; CPR = calibrated population resistance; DOR = doravirine; EFV = efavirenz; ETR = etravirine; F = female; FTC = emtricitabine; HIVdb = Stanford HIV Resistance Database; ID = identification number; IAS-USA = International Antiviral Society, USA; LFU = lost to follow-up; M = male; NNRTIs = non-nucleoside reverse transcriptase inhibitors; NRTIs = nucleoside reverse transcriptase inhibitors; NVP = nevirapine; RPV = rilpivirine; TDF = tenofovir; TLD = tenofovir, lamivudine, and dolutegravir; TND = target not detected; 3TC = lamivudine. Drugs in bold denote high resistance.
HIVdb algorithm v. 9.
IAS-USA list.
CPR tool.
Denotes low-level resistance.
Denotes intermediate-level resistance.
Reverse transcriptase–associated mutation.
The overall prevalence of NNRTI mutations was 10.2% (18/177); the most frequent NNRTI mutations were E138A/K (2.8%; 5/177), A98G (1.7%; 3/177), K103N (1.7%; 3/177), K101H/E (1.7%; 3/177), V179D (1.7%; 3/177), G190A (0.6%; 1/177), Y181C (0.6%; 1/177), L100I (0.6%; 1/177), V108I (0.6%; 1/177), and L234I (0.6; 1/177). The overall prevalence of NRTI mutations was low at 1.1% (2/177) and included M184MLV, D67N, K70R, and K219E.
Protease-associated mutations.
We did not get any major protease inhibitor (PI) mutations in any of the samples; however, minor or accessory PI mutations were found, such as L10F (2.8%; 5/177), L10I (1.7%; 3/177), Q58E (1.1%; 2/177), H69K (96.6%; 171/177), M36I (70.6%; 125/177), I93L (89.8%; 159/177), L89M (71.2%; 126/177), K20R (13.6%; 20/177), and M36V (4%; 7/177) (Table 3).
Table 3.
Drug resistance mutations associated with protease gene in treatment-naive PLHIV
| Wild-Type Amino Acid Position | Mutated Amino Acid | Total No. (%) (N = 177) | Resistance |
|---|---|---|---|
| L10 | F | 5 (2.8%) | DRV,* FPV,*† IDV,* LPV,*† NFV,*† ATV† |
| L10 | I | 3 (1.7%) | FPV,† IDV,† LPV,† NFV,† SQV† |
| K20 | R | 24 (13.6%) | IDV,† LPV,† |
| K20 | M | 2 (1.1%) | IDV,† LPV† |
| L23 | I‡ | 1 (0.6%) | NFV* |
| M36 | I | 125 (70.6%) | IDV,† NFV,† TPV† |
| M36 | V | 7 (4%) | TPV† |
| M36 | L | 17 (9.6%) | TPV† |
| Q58 | E | 2 (1.1%) | TPV*† |
| I62 | V | 2 (1.1%) | SQV† |
| H69 | K, R | 171 (96.6%), 2 (1.1%) |
TPV† |
| A71 | V, T | 1 (0.6%), 1 (0.6%) | IDV,† LPV,† NFV† |
| L89 | M, I | 126 (71.2%), 4 (2.3%) | TPV† |
| I93 | L | 159 (89.8%) | ATV† |
ATV = atazanavir; CPR = calibrated population resistance; DRV = darunavir; FPV = fosamprenavir; IAS-USA = International Antiviral Society, USA; IDV = indinavir; LPV = lopinavir; N = total number of patients; NFV = Nelfinavir; PLHIV = people living with HIV; SQV = saquinavir; TPV = tipranavir.
Resistance was analyzed using the Stanford HIV Resistance Database v. 9.
Resistance was analyzed using the IAS-USA mutation list 2022.
CPR tool.
DISCUSSION
In our study, the overall prevalence of PDR was 10.7% (19/177), with a very high prevalence of NNRTI mutations (10.2%) in treatment-naive PLHIV. Most studies assessing the prevalence of PDR in India were done between 2007 and 2013, with the prevalence varying from 0% to 20.58%,2,20–32 making our study one of the largest with the most recent data for the country. This wide variation in PDRs in the above studies could be due to difference in the years of sampling, sample size, drug resistance interpretation method, and reference list of resistance mutations used.
The country has been using NNRTIs as part of its first-line regimen since the inception of the program in 2004, when nevirapine was used, which was changed to efavirenz in 2014. The high prevalence of NNRTI DRMs in our samples from 2017 supports the change from NNRTI-based therapy to the integrase strand transfer inhibitors-based first-line regimen recommended by the National HIV treatment guidelines in 2021.
The overall prevalence of NRTI mutations was low at 1.1% (2/177), which is in agreement with a previous study done in 2014 in India in which the prevalence of NRTI mutations was 1.2% (2/170).29 Similar findings were observed in studies from Ethiopia,33,34 Brazil,35 and India.23 Mutations such as M184MLV, D67N, K70R, and K219E in our study were also detected in other studies from India.36,37 Studies have shown that over the past couple of years, the prevalence of NNRTI mutations, rather than NRTI mutations, has increased significantly in the country.29 Many of the mutations associated with NRTIs affect viral fitness and are less likely to persist without drug pressure; this could explain why they are often not found in PDR samples. Nevertheless, the finding of low prevalence of NRTI mutations in treatment-naive PLHIV suggests that they are still effective and should be part of the recommended first-line regimen.
None of our samples had major PI mutations, but we found extensive polymorphisms in the PR gene, which is consistent with findings from other Indian reports.20,21,32,37–40 Polymorphisms detected were H69K (96.6%; 171/177), M36I/L/V (84.2%; 149/177), I93L (89.8%; 159/177), L89M (71.2%; 126/177), L63P (56%; 99/177), I15V (41.2%; 73/177), and K20R (13.6%; 20/177). Among the mutations identified, the pattern of M36I/L/V, H69K, and L89M associated with drug resistance to tipranavir (TPV) was most frequently observed.41 The L63P (leucine-to-proline) mutation, which greatly increases HIV-1 replicative fitness under ART pressure, has been quite widespread in Indian PR sequences and elsewhere.42–44 We detected 89.83% of I93L mutations in our samples, which is linked to low levels of atazanavir (ATV) resistance per the IAS-USA mutation list. This is concerning, as ATV is part of the current second-line regimen recommended by the National AIDS Control Organisation.45 This, known accessory mutations or resistance-related mutations, may not imply PDR but may represent natural HIV-1 genetic diversity, with clinical relevance if present in combination with other mutations.34
Most of the participants in our study (98.8%) were infected with HIV-1 subtype C virus. This finding is similar to the prevalence of HIV-1 subtype C in other studies from India.20,21,46
Limitations of this study are that the sample collection was done in 2017 and it was from a single center; therefore, the isolates may not reflect current circulating strains in the country. However, none of the published studies from India have included patient samples after 2013, making these the most current data, and they support the recent change of NNRTI-based regimens to non–NNRTI-based regimens in the national guidelines. Because PLHIV in the program receive the same regimen across the country, it is likely that similar mutations are present in other regions, too.
CONCLUSION
In conclusion, our study revealed that the prevalence of NNRTI DRMs was 10.2% in a large center providing ART to >6,000 patients for the last 16 years; this is above the 10% threshold required by the WHO to change the first-line regimen from NNRTI based to non–NNRTI based. Therefore, the shift in the first-line regimen from efavirenz to dolutegravir by the program in 2021 seems to have come at the right time. Implementation of periodic nationwide HIV drug resistance surveys is the need of the hour in India to optimize ART regimens and to achieve the third goal of suppressing viral load in 95% of patients on ART.
ACKNOWLEDGMENTS
We thank UPSACS (Uttar Pradesh State AIDS Control Society) for its cooperation and Jan Albert, Karolinska Institute, Sweden for assistance with establishing the HIV resistance test. We also offer sincere thanks to all the patients and staff of the ART center who participated in this research work. We thank Shashi Bhushan Chauhan and Abhishek Kumar Singh for their help. The American Society of Tropical Medicine and Hygiene (ASTMH) assisted with publication expenses.
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