Genotypic Methods for HIV Drug Resistance Monitoring: The Opportunities and Challenges Faced by China

2019 ◽  
Vol 17 (4) ◽  
pp. 225-239 ◽  
Author(s):  
Lulu Zuo ◽  
Ke Peng ◽  
Yihong Hu ◽  
Qinggang Xu
Keyword(s):  
Drug Resistance ◽  
Virological Suppression ◽  
Testing Methods ◽  
Hiv Drug Resistance ◽  
Advantages And Disadvantages ◽  
Hiv Epidemic ◽  
Routine Surveillance ◽  
The World ◽  
Global Project ◽  
Hiv 1

AIDS is a globalized infectious disease. In 2014, UNAIDS launched a global project of “90-90-90” to end the HIV epidemic by 2030. The second and third 90 require 90% of HIV-1 infected individuals receiving antiretroviral therapy (ART) and durable virological suppression. However, wide use of ART will greatly increase the emergence and spreading of HIV drug resistance and current HIV drug resistance test (DRT) assays in China are seriously lagging behind, hindering to achieve virological suppression. Therefore, recommending an appropriate HIV DRT method is critical for HIV routine surveillance and prevention in China. In this review, we summarized the current existing HIV drug resistance genotypic testing methods around the world and discussed the advantages and disadvantages of these methods.

HIV drug resistance in newly diagnosed adults in a rural prefecture of eastern China

2014 ◽  
Vol 143 (3) ◽  
pp. 663-672 ◽  
Author(s):  
J. HUA ◽  
H. LIN ◽  
Y. DING ◽  
D. QIU ◽  
F. WONG ◽  
...  
Keyword(s):  
Drug Resistance ◽  
High Frequency ◽  
Eastern China ◽  
Scaling Up ◽  
Genetic Mutations ◽  
Newly Diagnosed ◽  
Hiv Drug Resistance ◽  
Subtype B ◽  
Hiv Epidemic ◽  
Hiv 1

SUMMARYLittle is known about HIV drug resistance (HIVDR) in newly diagnosed HIV-infected adults in eastern China where the HIV epidemic is spreading predominantly through sexual contact. During 2008–2011, newly HIV-diagnosed adults in Taizhou prefecture, Zhejiang province in eastern China were examined for HIVDR by amplifying and sequencing the HIV-1 pol gene. Of 447 genotyped participants, 53·7% were infected with CRF01_AE, 20·1% with CRF07_BC, 12·5% with subtype B, and 11·6% with CRF08_BC. Most of the participants had one or more minor genetic mutations in the pol gene that are associated with HIVDR. Twelve (2·7%) participants met the standard guidelines of having low to high HIVDR, suggesting that the prevalence of HIVDR in newly HIV-diagnosed adults was low in the study area and current antiretroviral therapy (ART) regimens are likely to remain effective. However, given high frequency of minor HIVDR in HIV patients and the scaling up of ART programmes in China, larger HIVDR surveillance programmes are needed.

scholarly journals Factors Influencing HIV Drug Resistance among Pregnant Women in Luanda, Angola: Findings from a Cross-Sectional Study

2021 ◽  
Vol 6 (1) ◽  
pp. 29
Author(s):  
Cruz S. Sebastião ◽  
Joana Morais ◽  
Miguel Brito
Keyword(s):  
Drug Resistance ◽  
Pregnant Women ◽  
Rural Areas ◽  
Cross Sectional Study ◽  
Drug Resistant ◽  
Sectional Study ◽  
Cross Sectional ◽  
Hiv Drug Resistance ◽  
Hiv 1 ◽  
High Educational

The increase in HIV infection and drug-resistant strains is an important public health concern, especially in resource-limited settings. However, the identification of factors related to the propagation of infectious diseases represents a crucial target offering an opportunity to reduce health care costs as well as deepening the focus on preventing infection in high-risk groups. In this study, we investigate the factors related to drug resistance among HIV-infected pregnant women in Luanda, the capital city of Angola. This was a part of a cross-sectional study conducted with 42 HIV-positive pregnant women. A blood sample was collected, and HIV-1 genotyping was carried out using an in-house method. Multivariate analyses were performed to determine the interaction between sociodemographic characteristics and drug resistance. HIV drug resistance was detected in 44.1% of the studied population. High probabilities of drug resistance were observed for HIV-infected pregnant women living in rural areas (AOR: 2.73; 95% CI: 0.50–14.9) with high educational level (AOR: 6.27; 95% CI: 0.77–51.2) and comorbidities (AOR: 5.47; 95% CI: 0.28–106) and infected with a HIV-1 non-B subtype other than subtype C (AOR: 1.60; 95% CI: 0.25–10.3). The present study reports high HIV drug resistance. Furthermore, older-age, rural areas, high educational levels, unemployed status, having comorbidities, and HIV-1 subtypes were factors related to drug resistance. These factors impact on drug susceptibility and need to be urgently addressed in order to promote health education campaigns able to prevent the spread of drug-resistant HIV strains in Angola.

scholarly journals Rates and Correlates of Short Term Virologic Response among Treatment-Naïve HIV-Infected Children Initiating Antiretroviral Therapy in Ethiopia: A Multi-Center Prospective Cohort Study

Pathogens ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 161
Author(s):  
Birkneh Tilahun Tadesse ◽  
Adugna Chala ◽  
Jackson Mukonzo ◽  
Tolosssa Eticha Chaka ◽  
Sintayehu Tadesse ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Viral Load ◽  
Plasma Viral Load ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Virological Suppression ◽  
Virologic Suppression ◽  
Hiv Drug Resistance ◽  
Treatment Naïve ◽  
The Impact

There is limited data on virologic outcome and its correlates among HIV-infected children in resource-limited settings. We investigated rate and correlates of virologic outcome among treatment naïve HIV-infected Ethiopian children initiating cART, and were followed prospectively at baseline, 8, 12, 24 and 48 weeks using plasma viral load, clinical examination, laboratory tests and pretreatment HIV drug resistance (PDR) screening. Virologic outcome was assessed using two endpoints–virological suppression defined as having “undetectable” plasma viral load < 150 RNA copies/mL, and rebound defined as viral load ≥150 copies/mL after achieving suppression. Cox Proportional Hazards Regression was employed to assess correlates of outcome. At the end of follow up, virologic outcome was measured for 110 participants. Overall, 94(85.5%) achieved virological suppression, of which 36(38.3%) experienced virologic rebound. At 48 weeks, 9(8.2%) children developed WHO-defined virological treatment failure. Taking tenofovir-containing regimen (Hazard Ratio (HR) 3.1-[95% confidence interval (95%CI) 1.0–9.6], p = 0.049) and absence of pretreatment HIV drug resistance (HR 11.7-[95%CI 1.3–104.2], p = 0.028) were independently associated with earlier virologic suppression. In conclusion, PDR and cART regimen type correlate with rate of virologic suppression which was prominent during the first year of cART initiation. However, the impact of viral rebound in 38.3% of the children needs evaluation.

scholarly journals Detection of novel HIV-1 drug resistance mutations by support vector analysis of deep sequence data and experimental validation

2019 ◽  
Author(s):  
Mariano Avino ◽  
Emmanuel Ndashimye ◽  
Daniel J. Lizotte ◽  
Abayomi S. Olabode ◽  
Richard M. Gibson ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Drug Treatment ◽  
Treatment Outcomes ◽  
Sequence Data ◽  
Wild Type Virus ◽  
Support Vector ◽  
Wild Type ◽  
Subtype B ◽  
The World ◽  
Hiv 1

AbstractThe global HIV-1 pandemic comprises many genetically divergent subtypes. Most of our understanding of drug resistance in HIV-1 derives from subtype B, which predominates in North America and western Europe. However, about 90% of the pandemic represents non-subtype B infections. Here, we use deep sequencing to analyze HIV-1 from infected individuals in Uganda who were either treatment-naïve or who experienced virologic failure on ART without the expected patterns of drug resistance. Our objective was to detect potentially novel associations between mutations in HIV-1 integrase and treatment outcomes in Uganda, where most infections are subtypes A or D. We retrieved a total of 380 archived plasma samples from patients at the Joint Clinical Research Centre (Kampala), of which 328 were integrase inhibitor-naïve and 52 were raltegravir (RAL)-based treatment failures. Next, we developed a bioinformatic pipeline for alignment and variant calling of the deep sequence data obtained from these samples from a MiSeq platform (Illumina). To detect associations between within-patient polymorphisms and treatment outcomes, we used a support vector machine (SVM) for feature selection with multiple imputation to account for partial reads and low quality base calls. Candidate point mutations of interest were experimentally introduced into the HIV-1 subtype B NL4-3 backbone to determine susceptibility to RAL in U87.CD4.CXCR4 cells. Finally, we carried out replication capacity experiments with wild-type and mutant viruses in TZM-bl cells in the presence and absence of RAL. Our analyses not only identified the known major mutation N155H and accessory mutations G163R and V151I, but also novel mutations I203M and I208L as most highly associated with RAL failure. The I203M and I208L mutations resulted in significantly decreased susceptibility to RAL (44.0-fold and 54.9-fold, respectively) compared to wild-type virus (EC50=0.32 nM), and may represent novel pathways of HIV-1 resistance to modern treatments.Author summaryThere are many different types of HIV-1 around the world. Most of the research on how HIV-1 can become resistant to drug treatment has focused on the type (B) that is the most common in high-income countries. However, about 90% of infections around the world are caused by a type other than B. We used next-generation sequencing to analyze samples of HIV-1 from patients in Uganda (mostly infected by types A and D) for whom drug treatment failed to work, and whose infections did not fit the classic pattern of adaptation based on B. Next, we used machine learning to detect mutations in these virus populations that could explain the treatment outcomes. Finally, we experimentally added two candidate mutations identified by our analysis to a laboratory strain of HIV-1 and confirmed that they conferred drug resistance to the virus. Our study reveals new pathways that other types of HIV-1 may use to evolve resistance to drugs that make up the current recommended treatment for newly diagnosed individuals.

scholarly journals Comparison of HIV drug resistance profiles across HIV-1 subtypes A and D for patients receiving a tenofovir-based and zidovudine-based first line regimens in Uganda

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Alisen Ayitewala ◽  
Fred Kyeyune ◽  
Pamela Ainembabazi ◽  
Eva Nabulime ◽  
Charles Drago Kato ◽  
...  
Keyword(s):  
Drug Resistance ◽  
First Line ◽  
Hiv Drug Resistance ◽  
Hiv 1

scholarly journals Drug resistance and tropism as markers of the dynamics of HIV-1 DNA quasispecies in blood cells of heavily pretreated patients who achieved sustained virological suppression

2015 ◽  
Vol 71 (3) ◽  
pp. 751-761 ◽  
Author(s):  
Pierre Gantner ◽  
Laurence Morand-Joubert ◽  
Charlotte Sueur ◽  
François Raffi ◽  
Catherine Fagard ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Blood Cells ◽  
Virological Suppression ◽  
Heavily Pretreated ◽  
Pretreated Patients ◽  
Hiv 1

scholarly journals Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

2020 ◽  
Author(s):  
Susana Posada-Céspedes ◽  
Gert Van Zyl ◽  
Hesam Montazeri ◽  
Jack Kuipers ◽  
Soo-Yon Rhee ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Genotype Data ◽  
Resistance Mutations ◽  
Subtype C ◽  
Cross Sectional ◽  
Data Set ◽  
Hiv Drug Resistance ◽  
Subtype B ◽  
Hiv 1 ◽  
Temporal Ordering

AbstractAlthough combination antiretoviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Here, we present a methodology for the comparison of mutational pathways in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational pathways from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models on a large number of resistance mutations and develop a statistical test to assess differences in the inferred mutational pathways between two groups. We apply this method to the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional data set of South African individuals living with HIV-1 subtype C, as well as a genotype data set of subtype B infections derived from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. Our results also show that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Furthermore, the maximum likelihood mutational networks for subtypes B and C share only 7 edges (Jaccard distance 0.802) and imply many different evolutionary pathways. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational pathways between any two groups.Author summaryThere is a disparity in the distribution of infections by HIV-1 subtype in the world. Subtype B is predominant in America, Western Europe and Australia, and most therapeutic strategies are based on research and clinical studies on this subtype. However, non-B subtypes represent the majority of global HIV-1 infections; e.g., subtype C alone accounts for nearly half of all HIV-1 infections. We present a statistical framework enabling the comparison of patterns of accumulating mutations in different HIV-1 subtypes. Specifically, we study lopinavir resistance pathways in HIV-1 subtypes B versus C, but the methodology can be generally applied to compare the temporal ordering of genetic events in different subgroups.

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