Comparison of HIV-1 RNA and HIV-1 DNA Genotypic Drug Resistance Testing in Women of Childbearing Age Infected with HIV-1 in Liangshan Prefecture

Abstract

This study focuses on women of childbearing age infected with HIV-1 in Liangshan Prefecture and analyses their HIV-1 RNA and HIV-1 DNA genotypic drug resistance to provide a theoretical basis and technical support for monitoring the spread of resistant strains and formulating and optimizing antiretroviral therapy regimens. The study subjects were women of childbearing age infected with HIV-1 who were followed up in the county of Liangshan Prefecture from January to September 2023. Peripheral venous blood samples were collected from each subject. The samples were centrifuged to separate the plasma and blood cells for HIV-1 RNA quantitative testing and HIV-1 genotypic drug resistance testing. A total of 47 participants were included in this study. When HIV-1 RNA were <50 copies/mL and between 50 and 1,000 copies/mL, the success rate of HIV-1 DNA pol gene amplification was significantly higher than that of HIV-1 RNA pol gene amplification. Among the 47 subjects, 17 (17/47, 36.17%) indicated successfully amplified HIV-1 RNA and HIV-1 DNA genotypic drug resistance in each region simultaneously, and 9 (9/17, 52.94%) developed any degree of resistance. Among these nine cases, five had consistent resistance, while four indicated inconsistent resistance. Among the five cases with identical drug resistance, there were three cases with inconsistent drug resistance mutations (DRMs). Among the four cases with inconsistent drug resistance results, one had DRMs at the HIV-1 DNA level but no DRMs at the HIV-1 RNA level, while the other three had more DRMs at the HIV-1 RNA level than at the HIV-1 DNA level. The combination of HIV-1 RNA and HIV-1 DNA genotypic drug resistance testing can improve the drawbacks of current single HIV-1 RNA genotypic drug resistance testing, especially when HIV-1 RNA is ≤1,000 copies/mL, and significantly improve the efficiency of HIV-1 genotypic drug resistance testing.

Introduction

HIV is mainly transmitted through blood, sexual contact, and from mother to child. HIV primarily targets the human immune system, causing a range of opportunistic infections and tumors, ultimately culminating in the patient’s demise. Antiretroviral therapy (ART) is the first-line treatment for HIV-1 infection.^1,2 Plasma HIV-1 RNA is the primary means of evaluating HIV-1 replication and ART efficacy, and inhibition of plasma HIV-1 RNA below the standard limit of <50 copies/mL is indicative of ART success.^3
–5 HIV-1 drug resistance is a major cause of ART failure, and timely drug resistance testing of individuals infected with HIV-1 is essential to predict ART failure.^6,7 Furthermore, the results of HIV-1 drug resistance testing can provide a reference for the formulation and adjustment of ART regimens.^8,9 The HIV-1 drug resistance testing methods include genotypic and phenotypic drug resistance testing, where the former is widely used domestically and internationally.^10,11 At present, HIV-1 genotypic drug resistance testing can be conducted at HIV-1 RNA and HIV-1 DNA levels.^12,13 When HIV-1 RNA levels are low or below the detection limit, the failure rate of conventional amplification of HIV-1 RNA is high, often making the HIV-1 RNA genotypic drug resistance testing impossible. According to the current Department of Health and Human Services (DHHS) guidelines, HIV-1 DNA genotypic drug resistance testing can be performed when the HIV-1 RNA levels are low or below the detection limit.¹⁴ In our previous research, we found that HIV-1 RNA genotypic drug resistance testing combined with HIV-1 DNA genotypic drug resistance testing can improve the success rate of drug resistance testing in patients with low-level viremia (LLV).¹⁵

Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) is located in southwestern China, which is the largest autonomous region of the Yi ethnic group in China. Since the first HIV-1-infected individual was reported in 1995, the AIDS epidemic has spread rapidly in the local area due to the influence of the natural geographical environment, traditional culture, sexual customs, health economy, and other factors.¹⁶ The AIDS epidemic has become one of the most serious public health events that endanger the local people. Since HIV-1-positive women of childbearing age (15–49 years old) may transmit HIV-1 to their infants during pregnancy, childbirth, and postpartum breastfeeding, it is even more necessary to improve the quality of their antiviral treatment.¹⁷ This study focuses on HIV-1-infected women of childbearing age in Liangshan Prefecture and analyses their HIV-1 RNA and HIV-1 DNA genotypic drug resistance to provide a theoretical basis and technical support for monitoring the spread of resistant strains and formulating and optimizing ART regimens.

Subjects and Methods

Study subject

This study includes individuals infected with HIV-1 who were followed up in the county of Liangshan Prefecture from January to September 2023. Inclusion criteria: (1) female aged 15–49 years old; (2) undergoing ART for ≥6 months; (3) were tested for HIV-1 RNA and HIV-1 DNA genotypic drug resistance simultaneously; and (4) all subjects, or their guardians provided informed consent. Cases with incomplete clinical data were excluded. This study was approved by the Medical Ethics Committee of the First People’s Hospital of Yuexi County (No. KY202212-02).

Method

Specimen collection

Peripheral venous blood (10 mL) was collected from each subject using an ethylenediaminetetraacetic acid (EDTA) K₂ anti-coagulant blood collection vessel, centrifuged at 500×g for 10 min; plasma and blood cells were then separated using sterile Pasteur straws. The separated plasma and blood cells were stored at −80°C ultra-low temperature refrigerator for subsequent testing. The plasma and blood cells were sent to Dongguan Institute for Microscale and Precision Medical Measurement for HIV-1 RNA quantitative testing and HIV-1 genotypic drug resistance testing.

HIV-1 RNA quantitative testing

Briefly, the plasma HIV-1 RNA was extracted and then quantitatively analyzed via real-time quantitative reverse transcription PCR method.

HIV-1 genotypic drug resistance testing

The main steps included (1) plasma HIV-1 RNA and blood cell HIV-1 DNA extraction; (2) the HIV-1 pol gene was amplified with the in-house HIV-1 genotypic drug resistance testing method (the fragment lengths of the amplified protease and reverse transcriptase (PR/RT) region and integrase (IN) region were all around 1100 bp); (3) Sanger sequencing of PCR products; and (4) the Stanford University HIV Drug Resistance Database (https://hivdb.stanford.edu) was used to identify the drug resistance mutations (DRMs), and degree of drug resistance to different drugs. Based on the scoring criteria, the degree of drug resistance was divided into sensitivity, potential low-level resistance, low-level resistance, intermediate resistance, and high-level resistance. In the case of low-level resistance, intermediate or high-level resistance levels were used to determine drug resistance. In the same subject, if the DRMs detected at both the HIV-1 RNA and HIV-1 DNA levels were exactly the same, they were defined as consistent DRMs; otherwise, they were defined as inconsistent DRMs. All sequences had been deposited in GenBank (accession numbers PQ652325 to PQ652342).

HIV-1 subtype identification

The sequences were submitted to the HIV BLAST tool in the HIV Sequence Database (https://www.hiv.lanl.gov/content/sequence/BASIC_BLAST/basic_blast.html) for HIV-1 subtype identification.

Construction of phylogenetic tree

For subjects with low-level or above low-level resistance, their PR/RT and IN sequences of HIV-1 RNA and HIV-1 DNA were merged into one sequence, respectively. The MAFFT software was used for multiple sequence alignment. The IQ-TREE software was used to construct a phylogenetic tree via the maximum likelihood method, the built-in ModelFinder was used to find the optimal model GTR + F + I + G4, and the bootstrap value was set to 1,000 times. The FigTree was used to beautify the phylogenetic tree.

Clinical data collection

The data of age, HIV-1 infection pathway, ART initiation time, initial ART regimen, whether ART regimen was adjusted, and current ART regimen of study subjects were collected.

Statistical analysis

The SPSS 24.0 software was used for data organization and statistical analysis. The counting data were expressed in frequency and percentage. The inter-group comparisons were performed with the help of Fisher’s exact test. All tests were conducted using a bilateral test, with p < .05 indicating statistically significant differences.

Results

Basic information

Based on the inclusion criteria, 47 participants with a median age of 37 years old (15–48 years old) were included in the study. Of these, 36 cases (36/47, 76.60%) were infected through sexual transmission, whereas 11 cases (11/47, 23.40%) indicated non-sexual transmission of HIV-1. There were 3 cases (3/47, 6.38%) with ART time between 0.5 and <2 years, 7 cases (7/47, 14.89%) between 2 and <4 years, 24 cases (24/47, 51.07%) between 4 and <6 years, and 13 cases (13/47, 27.66%) with ≥6 years. In the ART regimens, two types of nucleoside reverse transcriptase inhibitors (NRTI) + one type of non-nucleoside reverse transcriptase inhibitor (NNRTI) were the main ART regimens (33/47, 70.21%).

Comparison of successful amplification rates of HIV-1 RNA and HIV-1 DNA pol gene at different levels of HIV-1 RNA

Among the 47 participants, 16 (16/47, 34.04%) indicated <50 copies/mL, 17 (17/47, 36.17%) had between 50 and 1,000 copies/mL, and 14 (14/47, 29.79%) presented >1,000 copies/mL of HIV-1 RNA. When HIV-1 RNA were <50 copies/mL and between 50 and 1,000 copies/mL, the success rate of HIV-1 DNA pol gene amplification was significantly higher than that of HIV-1 RNA pol gene amplification, and the difference was statistically significant (p < .001; p = .003) (Table 1).

Table 1.

Comparison of Successful Amplification Rates of HIV-1 RNA and HIV-1 DNA pol Gene at Different Levels of HIV-1 RNA

HIV-1 RNA (copies/mL)	n	Successful amplification of HIV-1 RNA pol gene (n [%])	Successful amplification of HIV-1 DNA pol gene (n [%])	p value
<50	16	0 (0)	15 (93.75)	<.001
50–1,000	17	9 (52.94)	17 (100)	.003
>1,000	14	14 (100)	14 (100)	—

Comparison of successful amplification rates in different regions of HIV-1 RNA and HIV-1 DNA pol gene at different levels of HIV-1 RNA

When HIV-1 RNA were <50 copies/mL and between 50 and 1,000 copies/mL, the success rate of the PR/RT region of HIV-1 DNA amplification was significantly higher than that of the PR/RT region of HIV-1 RNA amplification, and the difference was statistically significant (p < .001; p = .001). However, we only found that the success rate of the IN region of HIV-1 DNA amplification was significantly higher than that of the IN region of HIV-1 RNA amplification when HIV-1 RNA was <50 copies/mL, and the difference was statistically significant (p < .001) (Table 2).

Table 2.

Comparison of Successful Amplification Rates in Different Regions of HIV-1 RNA and HIV-1 DNA pol Gene at Different Levels of HIV-1 RNA

HIV-1 RNA (copies/mL)	n	RT region (n [%])			PR region (n [%])			IN region (n [%])
HIV-1 RNA (copies/mL)	n	HIV-1 RNA	HIV-1 DNA	p value	HIV-1 RNA	HIV-1 DNA	p value	HIV-1 RNA	HIV-1 DNA	p value
<50	16	0 (0)	15 (93.75)	<.001	0 (0)	15 (93.75)	<.001	0 (0)	11 (68.75)	<.001
50–1,000	17	6 (35.29)	16 (94.12)	.001	6 (35.29)	16 (94.12)	.001	8 (47.06)	13 (76.47)	.157
>1,000	14	14 (100)	14 (100)	—	14 (100)	14 (100)	—	13 (92.86)	14 (100)	.000

IN, integrase; PR, protease; RT, reverse transcriptase.

Consistency analysis of genotypic drug resistance testing for HIV-1 RNA and HIV-1 DNA

Among the 47 subjects, 17 (17/47, 36.17%) indicated successfully amplified HIV-1 RNA and HIV-1 DNA genotypic drug resistance in each region simultaneously, and 9 (9/17, 52.94%) developed any degree of resistance. Among these nine cases, five had consistent resistance, while four indicated inconsistent resistance (Table 3). Among the five cases with identical drug resistance, there were three cases with inconsistent DRMs (Table 4). Among the four cases with inconsistent drug resistance, one had DRMs at the HIV-1 DNA level but no DRMs at the HIV-1 RNA level, while the other three had more DRMs at the HIV-1 RNA level than at the HIV-1 DNA level (Table 5). Figure 1 indicates the phylogenetic tree of HIV-1 RNA and HIV-1 DNA pol gene (PR/RT and IN regions) amplified fragments from these nine cases (Fig. 1).

FIG. 1.

Phylogenetic tree of HIV-1 RNA and HIV-1 DNA pol gene (PR/RT and IN regions) amplified fragments from these nine cases. IN, integrase; PR, protease; RT, reverse transcriptase.

Table 3.

Consistency Analysis of Genotypic Drug Resistance Testing for HIV-1 RNA and HIV-1 DNA

HIV-1 RNA (copies/mL)	n	Consistent results of genotypic drug resistance testing for HIV-1 RNA and HIV-1 DNA (n [%])	Inconsistent results of genotypic drug resistance testing for HIV-1 RNA and HIV-1 DNA (n [%])
<50	0	0 (0)	0 (0)
50–1,000	3	0 (0)	3 (100)
>1,000	6	5 (83.33)	1 (16.67)

Table 4.

Consistency Analysis of Drug-Resistant Drugs for HIV-1 RNA and HIV-1 DNA

No.	HIV-1 RNA (copies/mL)	HIV-1 RNA sample				HIV-1 DNA sample
No.	HIV-1 RNA (copies/mL)	RT region	PR region	IN region	Drug-resistant drugs	RT region	PR region	IN region	Drug-resistant drugs
1	122,400	D67G, S68G, K70R, M184V, T215F, K219E, L100I, K103N	S	S	H: ABC, AZT, d4T, ddI, FTC, 3TC, EFV, NVP, RPV; I: TDF, DOR, ETR	D67G, S68G, K70R, M184V, T215FIS, K219E, L100I, K103N	S	S	H: ABC,AZT, d4T, ddI, FTC, 3TC, EFV, NVP, RPV; I: TDF, DOR, ETR
2	42,720	D67N, K70E, M184V, K101E, V106M, V108I, H221Y, F227L	S	S	H: FTC, 3TC, DOR, EFV, NVP, RPV; I: ABC, d4T, ddI; L: TDF, ETR	D67N, K70E, M184V, K101E, V106M, V108I, H221Y, F227L	S	S	H: FTC, 3TC, DOR, EFV, NVP, RPV; I: ABC, d4T, ddI; L: TDF, ETR
3	3,270	M41L, K65R, S68DGN, K70T, M184V, K103S, V106M	S	S	H: ABC, d4T, ddI, FTC, 3TC, TDF, EFV, NVP; I: DOR	M41L, K65R, S68N, K70T, M184V, K103NRS, V106M	S	S	H: ABC, d4T, ddI, FTC, 3TC, TDF, EFV, NVP; I: DOR
4	3,288	K65R, Y115F, M184V, K219E, K103N, Y181C, G190A, H221Y	S	S	H: ABC, d4T, ddI, FTC, 3TC, TDF, EFV, ETR, NVP, RPV; I: DOR	K65R, S68KNR, Y115F, M184V, K219E, K103N, Y181C, G190A, H221Y	S	S	H: ABC, d4T, ddI, FTC, 3TC, TDF, EFV, ETR, NVP, RPV; I: DOR
5	13,020	V108I	S	S	L: NVP； P: DOR, EFV	V108I	S	S	L: NVP； P: DOR, EFV

3TC, lamivudine; ABC, abacavir; AZT, zidovudine; d4T, stavudine; ddI, didanosine; DOR, doravirine; EFV, efavirenz; ETR, etravirine; FTC, emtricitabine; H, high-level resistance; I, intermediate resistance; L, low-level resistance; NVP, nevirapine; P, potential low-level resistance; RPV, rilpivirine; S, sensitivity; TDF, tenofovir disoproxil fumarate.

Table 5.

Inconsistency Analysis of Drug-Resistant Drugs for HIV-1 RNA and HIV-1 DNA

No.	HIV-1 RNA (copies/mL)	HIV-1 RNA sample				HIV-1 DNA sample
No.	HIV-1 RNA (copies/mL)	RT region	PR region	IN region	Drug-resistant drugs	RT region	PR region	IN region	Drug-resistant drugs
6	159000	S	S	S	ND	H221Y	S	S	L: NVP, RPV; P: DOR, EFV, ETR
7	115	M184V, L210W, K219E, K101H, V108I, Y181C, G190A	S	A128T	H: FTC, 3TC, EFV, ETR, NVP, RPV; I: DOR; L: ABC, AZT, d4T, ddI	M184V, L210W, K219E, V108I, G190A	S	A128T	H: FTC, 3TC, NVP; I: EFV; L: ABC, AZT, d4T, ddI, RPV; P: DOR, ETR
8	828	K65R, K103N, P225H	S	S	H: d4T, ddI, EFV, NVP; I: ABC, FTC, 3TC, TDF, DOR	K103N	S	S	H: EFV, NVP
9	373	M184I, V106M, V179D	S	S	H: FTC, 3TC, EFV, NVP； I: DOR; L: ABC; P: ddI, ETR, RPV	V179D	S	S	P: EFV, ETR, NVP, RPV

“ND” indicates that no drug resistance was found.

HIV-1 subtype

Among the 46 subjects who successfully amplified the HIV-1 pol gene at the HIV-1 RNA or HIV-1 DNA level, there were 2 HIV-1 subtypes, among which CRF07_BC was the most dominant (45/46, 97.83%), followed by CRF08_BC (1/46, 2.17%).

Discussion

This study focuses on women of childbearing age infected with HIV-1 in Liangshan Prefecture and analyses their HIV-1 RNA and HIV-1 DNA genotypic drug resistance. Since the implementation of ART, significant progress has been made in the treatment of HIV-1 infection. However, due to the high HIV-1 replication rate and mutation frequency, as well as the host’s immune response and drug selection pressure, drug resistance has emerged.^18,19 The HIV-1 resistance occurs during the ART regimen when the drug target genes undergo mutations, resulting in the virus developing resistance and reduced sensitivity to the drug. The occurrence and development process of HIV-1 resistance is very complex, depending on the degree of sequence differences, the sustained virus replication, the ease of occurrence of DRMs, and the impact of DRMs on drug sensitivity. Furthermore, mutated resistance genes negatively affect the function of HIV-1, decreasing its infectivity and replication ability, ultimately resulting in changes in its transmission and pathogenicity.²⁰ Due to HIV-1 infection, women of childbearing age may transmit the virus to their infants during pregnancy, childbirth, and postpartum breastfeeding, which can seriously endanger the physical and mental health of these women and the newborn infant. However, good monitoring of HIV-1 resistance in infected women will help to strengthen the prevention of mother-to-child transmission of AIDS.

A study has found that when HIV-1 RNA is low, drug resistance testing against HIV-1 DNA can detect virological failure in LLV or guide simpliﬁed treatment.²¹ This study also found that when HIV-1 RNA <50 and between 50 and 1,000 copies/mL, the success rate of genes amplification in the pol of HIV-1 DNA was significantly higher than that of HIV-1 RNA. This is because HIV-1 DNA is relatively stable in cells and is not affected by the amount of free HIV-1 RNA in plasma.^22,23 Moreover, when the level of HIV-1 RNA is low or below the detection limit, HIV-1 DNA still has a high success rate in genes amplification, consistent with our previous research results.¹⁵

Comparing the success rates of amplification in different regions of HIV-1 RNA and HIV-1 DNA pol gene revealed that the success rate of resistance testing in the IN region is generally lower than that in the PR/RT region, consistent with Wenk et al.’s study.²⁴ Here, three cases with identical drug resistance showed inconsistent DRMs for HIV-1 RNA and HIV-1 DNA. The incomplete consistency of DRMs was due to differences in base pairs and the number of drug resistance sites; however, it did not cause the differences in resistance outcomes between the two. Furthermore, the phylogenetic tree revealed that HIV-1 RNA and HIV-1 DNA fragments in the PR/RT and IN regions of the same case can be clustered into small clusters (the bootstrap values were all 100) and had a genetic distance of <0.015, indicating that HIV-1 RNA and HIV-1 DNA amplification fragments have high consistency, which is similar to our previous research.¹⁵ Moreover, one case did not show a DRM at the HIV-1 RNA level but indicated at the HIV-1 DNA level, suggesting that HIV-1 DNA genotypic drug resistance testing may cover more resistance mutations.¹² However, four other cases indicated that there were more DRMs at the HIV-1 RNA level than at the HIV-1 DNA level, which might be because Sanger sequencing was used, which only detects dominant sequences. The principle of Sanger sequencing is to select the sequences with the highest abundance proportion for priority sequencing. The proportion of these dominant sequences theoretically needs to exceed 40% of the total number of sequences, which can explain the differences in DRMs at HIV-1 RNA and HIV-1 DNA levels.²⁵ Therefore, deep sequencing is necessary to detect undetected DRMs.

This study also had some limitations. First, this was a single-center study with a small sample size. Second, although Sanger sequencing is a classical sequencing method in clinics, it has relatively low sensitivity. In future research, we will enlarge the sample size and adopt a more sensitive sequencing method to validate this conclusion.

Conclusions

In summary, the combination of HIV-1 RNA and HIV-1 DNA genotypic drug resistance testing can improve the drawbacks of current single HIV-1 RNA genotypic drug resistance testing, especially when HIV-1 RNA is ≤1,000 copies/mL, and significantly improve the efficiency of HIV-1 genotypic drug resistance testing.

Footnotes

Authors’ Contributions

Data collection was conducted by S.S. and P.D. Data analysis and interpretation were conducted by B.C., M.L., and Y.Z. Drafting the article was conducted by B.C. Revising the article was conducted by F.H., Y.H., and L.Z. Study design and final approval of the article were conducted by L.Z.

Availability of Data and Materials

The data collected in this study will be available to external investigators interested in collaboration upon submission and approval of a data analysis plan. Requests for data should be submitted to zhongli620@163.com.

Author Disclosure Statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding Information

This work was supported by Chinese Association of STD & AIDS Prevention and Control·Maternal and Child Tigermed Care and Prevention of Maternal to Child Transmission Fund (PMTCT202207) and Doctoral Research Initiation Fund of Affiliated Hospital of Southwest Medical University.

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