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Sivay MV, Maksimenko LV, Nalimova TM, Nefedova AA, Osipova IP, Kriklivaya NP, Gashnikova MP, Ekushov VE, Totmenin AV, Kapustin DV, Pozdnyakova LL, Skudarnov SE, Ostapova TS, Yaschenko SV, Nazarova OI, Shevchenko VV, Ilyina EA, Novikova OA, Agafonov AP, Gashnikova NM. HIV drug resistance among patients experiencing antiretroviral therapy failure in Russia, 2019-2021. Int J Antimicrob Agents 2024; 63:107074. [PMID: 38154660 DOI: 10.1016/j.ijantimicag.2023.107074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 11/15/2023] [Accepted: 12/20/2023] [Indexed: 12/30/2023]
Abstract
Increasing HIV drug resistance is an important public health concern. The current study aimed to assess HIV drug resistance among people who live with HIV (PLWH) experiencing virological failure. Blood samples and epidemiological characteristics were collected in four Siberian regions from PLWH experiencing ART failure. Partial pol gene sequences were obtained for the study individuals. Drug resistance mutations (DRMs) were predicted using the Stanford HIVdb Program. The association of HIV DRM with epidemiological characteristics was estimated using logistic regression analysis. Further analysis was performed for children (0-14 y old) and adults (≥15 y old) separately. In total, 815 (89.4%) patients were included in the final dataset. Overall, 501 (61.5%) patients had DRM detected. NRTI DRM was more common in children, while NRTI+NNRTI DRM was more frequent in adults (P < 0.001). Krasnoyarsk region, male sex and high viral load were positively associated with the presence of DRM in adults, while higher CD4 cell count and PI/INSTI-based ART had a negative association. No association between epidemiological characteristics and DRM was identified in children. The remaining 38.5% of patients with virological failure had no DRM detected; those patients were likely to have insufficient ART adherence. Most (55.5%) patients had HIV CRF63_02A6, followed by sub-subtype A6 (39.2%). This study revealed poor ART adherence as a main factor driving ART failure among PLWH in the Siberian region. DRM was detected in over 60% of PLWH experiencing ART failure. The current results highlight an urgent need for the introduction of special programs focusing on ART adherence improvement.
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Affiliation(s)
- Mariya V Sivay
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia.
| | - Lada V Maksimenko
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Tatiana M Nalimova
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Anastasiya A Nefedova
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Irina P Osipova
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Nadezda P Kriklivaya
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Mariya P Gashnikova
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Vasiliy E Ekushov
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Alexei V Totmenin
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | | | | | - Sergey E Skudarnov
- Krasnoyarsk Regional Center for Prevention and Control of AIDS, Krasnoyarsk, Russia
| | - Tatyana S Ostapova
- Krasnoyarsk Regional Center for Prevention and Control of AIDS, Krasnoyarsk, Russia
| | - Svetlana V Yaschenko
- Krasnoyarsk Regional Center for Prevention and Control of AIDS, Krasnoyarsk, Russia
| | - Olga I Nazarova
- Omsk City Center for Prevention and Control of AIDS and Other Infectious Diseases, Omsk, Russia
| | - Valery V Shevchenko
- Altai Regional Center for Prevention and Control of AIDS and Other Infectious Diseases, Barnaul, Russia
| | - Elena A Ilyina
- Altai Regional Center for Prevention and Control of AIDS and Other Infectious Diseases, Barnaul, Russia
| | - Olga A Novikova
- Altai Regional Center for Prevention and Control of AIDS and Other Infectious Diseases, Barnaul, Russia
| | - Aleksander P Agafonov
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
| | - Natalya M Gashnikova
- State Research Center of Virology and Biotechnology 'Vector', Novosibirsk region, Russia
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2
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Chen H, Hao J, Hu J, Song C, Zhou Y, Li M, Chen J, Liu X, Wang D, Xu X, Xin P, Zhang J, Liao L, Feng Y, Li D, Pan SW, Shao Y, Ruan Y, Xing H. Pretreatment HIV Drug Resistance and the Molecular Transmission Network Among HIV-Positive Individuals in China in 2022: Multicenter Observational Study. JMIR Public Health Surveill 2023; 9:e50894. [PMID: 37976080 PMCID: PMC10692882 DOI: 10.2196/50894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/10/2023] [Accepted: 10/06/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND Emerging HIV drug resistance caused by increased usage of antiretroviral drugs (ARV) could jeopardize the success of standardized HIV management protocols in resource-limited settings. OBJECTIVE We aimed to characterize pretreatment HIV drug resistance (PDR) among HIV-positive individuals and risk factors in China in 2022. METHODS This cross-sectional study was conducted using 2-stage systematic sampling according to the World Health Organization's surveillance guidelines in 8 provincial-level administrative divisions in 2022. Demographic information and plasma samples were obtained from study participants. PDR was analyzed using the Stanford HIV drug resistance database, and the Tamura-Nei 93 model in HIV-TRACE was used to calculate pairwise matches with a genetic distance of 0.01 substitutions per site. Logistic regression was used to identify and estimate factors associated with PDR. RESULTS PDR testing was conducted on 2568 participants in 2022. Of the participants, 34.8% (n=893) were aged 30-49 years, 81.4% (n=2091) were male, and 3.2% (n=81) had prior ARV exposure. The prevalence of PDR to protease and reverse transcriptase regions, nonnucleoside reverse transcriptase inhibitors, nucleoside reverse transcriptase inhibitors, and protease inhibitors were 7.4% (n=190), 6.3% (n=163), 1.2% (n=32), and 0.2% (n=5), respectively. Yunnan, Jilin, and Zhejiang had much higher PDR incidence than did Sichuan. The prevalence of nonnucleoside reverse transcriptase inhibitor-related drug resistance was 6.1% (n=157) for efavirenz and 6.3% (n=163) for nevirapine. Multivariable logistic regression models indicated that participants who had prior ARV exposure (odds ratio [OR] 7.45, 95% CI 4.50-12.34) and the CRF55_01B HIV subtype (OR 2.61, 95% CI 1.41-4.83) were significantly associated with PDR. Among 618 (24.2%) sequences (nodes) associated with 253 molecular transmission clusters (size range 2-13), drug resistance mutation sites included K103, E138, V179, P225, V106, V108, L210, T215, P225, K238, and A98. CONCLUSIONS The overall prevalence of PDR in China in 2022 was modest. Targeted genotypic PDR testing and medication compliance interventions must be urgently expanded to address PDR among newly diagnosed people living with HIV in China.
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Affiliation(s)
- Hongli Chen
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
- Sichuan Nursing Vocational College, Chengdu, China
| | - Jingjing Hao
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Jing Hu
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Chang Song
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Yesheng Zhou
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Miaomiao Li
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Jin Chen
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Xiu Liu
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Dong Wang
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Xiaoshan Xu
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Peixian Xin
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Jiaxin Zhang
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Lingjie Liao
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Yi Feng
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Dan Li
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Stephen W Pan
- Department of Public Health, The University of Texas at San Antonio, San Antonio, TX, United States
| | - Yiming Shao
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Yuhua Ruan
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Hui Xing
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
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3
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Li M, Song C, Hu J, Dong A, Kang R, Feng Y, Xing H, Ruan Y, Shao Y, Hong K, Liao L. Impact of pretreatment low-abundance HIV-1 drug resistance on virological failure after 1 year of antiretroviral therapy in China. J Antimicrob Chemother 2023; 78:2743-2751. [PMID: 37769159 DOI: 10.1093/jac/dkad297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/14/2023] [Indexed: 09/30/2023] Open
Abstract
OBJECTIVES To assess the impact of pretreatment low-abundance HIV drug-resistant variants (LA-DRVs) on virological outcomes among ART-naive HIV-1-infected Chinese people who initiated ART. METHODS A nested case-control study was conducted among HIV-1-infected individuals who had pretreatment drug resistance (PDR) genotypic results. Cases were defined as individuals with virological failure (HIV-1 RNA viral load ≥1000 copies/mL) after 1 year of ART, and controls were individuals from the same cohort whose viral load was less than 1000 copies/mL. Next-generation sequencing was used to identify low-abundance PDR mutations at detection thresholds of 10%, 2% and 1%. The mutant load was calculated by multiplying the abundance of HIV-1 drug-resistant variants by the pretreatment viral load. The impact of pretreatment low-abundance mutations on virological failure was estimated in logistic regression models. RESULTS Participants (43 cases and 100 controls) were included in this study for the analysis. The proportion of participants with PDR was higher in cases than in controls at different detection thresholds (44.2% versus 22.0%, P = 0.007 at 10% threshold; 58.1% versus 31.0%, P = 0.002 at 2% threshold; 90.7% versus 69.0%, P = 0.006 at 1% threshold). Compared with participants without PDR, participants with ≥10% detectable PDR mutations were associated with an increased risk of virological failure (adjusted OR 8.0, 95% CI 2.4-26.3, P = 0.001). Besides this, individuals with pretreatment LA-DRVs (2%-9% abundance range) had 5-fold higher odds of virological failure (adjusted OR 5.0, 95% CI 1.3-19.6, P = 0.021). Furthermore, LA-DRVs at 2%-9% abundance resistant to NRTIs and mutants with abundance of ≥10% resistant to NNRTIs had a 4-fold and 8-fold risk of experiencing virological failure, respectively. It was also found that a mutant load of more than 1000 copies/mL was predictive of virological failure (adjusted OR 7.2, 95% CI 2.5-21.1, P = 0.0003). CONCLUSIONS Low-abundance PDR mutations ranging from 2% to 9% of abundance can increase the risk of virological failure. Further studies are warranted to define a clinically relevant threshold of LA-DRVs and the role of NRTI LA-DRVs.
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Affiliation(s)
- Miaomiao Li
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Chang Song
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Jing Hu
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Aobo Dong
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Ruihua Kang
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Yi Feng
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Hui Xing
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Yuhua Ruan
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Yiming Shao
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Kunxue Hong
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
| | - Lingjie Liao
- National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, China
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4
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Balakrishna S, Loosli T, Zaheri M, Frischknecht P, Huber M, Kusejko K, Yerly S, Leuzinger K, Perreau M, Ramette A, Wymant C, Fraser C, Kellam P, Gall A, Hirsch HH, Stoeckle M, Rauch A, Cavassini M, Bernasconi E, Notter J, Calmy A, Günthard HF, Metzner KJ, Kouyos RD. Frequency matters: comparison of drug resistance mutation detection by Sanger and next-generation sequencing in HIV-1. J Antimicrob Chemother 2023; 78:656-664. [PMID: 36738248 DOI: 10.1093/jac/dkac430] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 11/18/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Next-generation sequencing (NGS) is gradually replacing Sanger sequencing (SS) as the primary method for HIV genotypic resistance testing. However, there are limited systematic data on comparability of these methods in a clinical setting for the presence of low-abundance drug resistance mutations (DRMs) and their dependency on the variant-calling thresholds. METHODS To compare the HIV-DRMs detected by SS and NGS, we included participants enrolled in the Swiss HIV Cohort Study (SHCS) with SS and NGS sequences available with sample collection dates ≤7 days apart. We tested for the presence of HIV-DRMs and compared the agreement between SS and NGS at different variant-calling thresholds. RESULTS We included 594 pairs of SS and NGS from 527 SHCS participants. Males accounted for 80.5% of the participants, 76.3% were ART naive at sample collection and 78.1% of the sequences were subtype B. Overall, we observed a good agreement (Cohen's kappa >0.80) for HIV-DRMs for variant-calling thresholds ≥5%. We observed an increase in low-abundance HIV-DRMs detected at lower thresholds [28/417 (6.7%) at 10%-25% to 293/812 (36.1%) at 1%-2% threshold]. However, such low-abundance HIV-DRMs were overrepresented in ART-naive participants and were in most cases not detected in previously sampled sequences suggesting high sequencing error for thresholds <3%. CONCLUSIONS We found high concordance between SS and NGS but also a substantial number of low-abundance HIV-DRMs detected only by NGS at lower variant-calling thresholds. Our findings suggest that a substantial fraction of the low-abundance HIV-DRMs detected at thresholds <3% may represent sequencing errors and hence should not be overinterpreted in clinical practice.
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Affiliation(s)
- Suraj Balakrishna
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Tom Loosli
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Maryam Zaheri
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Swiss National Center for Retroviruses, University of Zurich, Zurich, Switzerland
| | - Paul Frischknecht
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Swiss National Center for Retroviruses, University of Zurich, Zurich, Switzerland
| | - Katharina Kusejko
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Sabine Yerly
- Laboratory of Virology, University Hospital Geneva, University of Geneva, Geneva, Switzerland
| | - Karoline Leuzinger
- Clinical Virology Division, Laboratory Medicine, University Hospital Basel, Basel, Switzerland
| | - Matthieu Perreau
- Division of Immunology and Allergy, University Hospital Lausanne, University of Lausanne, Lausanne, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Chris Wymant
- Nuffield Department of Medicine, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Christophe Fraser
- Nuffield Department of Medicine, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.,Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Paul Kellam
- Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London, UK
| | - Astrid Gall
- Excellence in Life Sciences (EMBO), Heidelberg, Germany
| | - Hans H Hirsch
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Marcel Stoeckle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Julia Notter
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Alexandra Calmy
- Division of Infectious Diseases, University Hospital Geneva, University of Geneva, Geneva, Switzerland
| | - Huldrych F Günthard
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Karin J Metzner
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Roger D Kouyos
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
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5
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Li Q, Yu F, Song C, Zhao H, Yan L, Xiao Q, Lao X, Yang S, Tang Y, Xiao J, Zhang F. A Concentration Method for HIV Drug Resistance Testing in Low-Level Viremia Samples. BIOMED RESEARCH INTERNATIONAL 2022; 2022:2100254. [PMID: 36467892 PMCID: PMC9711986 DOI: 10.1155/2022/2100254] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 10/15/2022] [Accepted: 10/27/2022] [Indexed: 08/08/2023]
Abstract
BACKGROUND Drug resistance testing in HIV-1 low-level viremia (LLV) samples is challenging yet critical. Our study is aimed at assessing the performance of lentivirus concentration reagent (LCR) in combination with a validated Sanger sequencing (SS) for monitoring drug resistance mutations (DRMs) in LLV samples. METHODS A series of clinical samples were diluted and amplified for genotypic resistance testing (GRT) to prove the performance of the LCR. The Stanford HIV-1 drug resistance database (HIVdb version 8.9) was used to analyze the mutations. HIV-1 subtypes and CRFs were determined using the COMET online tool. The overall success rate of genotyping was compared with ultracentrifugation combined with SS. Furthermore, the success rates at varied VL of the two concentration methods were evaluated, and the DRMs of diluted samples were compared with those undiluted samples. RESULTS When LCR was used, the overall success rate was 90% (72/80) in the PR and RT regions and 60% (48/80) in the IN region. In addition, when HIV RNA was 1000 copies/ml, 400 copies/ml, 200 copies/ml, and 100 copies/ml, the success rates of PR and RT regions were 100%, 100%, 95%, and 65%, respectively, while the success rates of IN region were 85%, 60%, 45%, and 50%, respectively. We found that the sample DR-387A2 missed the E138A mutation, and mutations in other samples were consistent with undiluted samples using LCR. CONCLUSIONS LCR will support monitoring DRMs in HIV-1 patients with LLV and can be an effective alternative for small- and medium-sized laboratories that cannot afford an ultracentrifuge.
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Affiliation(s)
- Qun Li
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Fengting Yu
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Chuan Song
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, China
| | - Hongxin Zhao
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Liting Yan
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Qing Xiao
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Xiaojie Lao
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Siyuan Yang
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Yunxia Tang
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Jiang Xiao
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
| | - Fujie Zhang
- Beijing Ditan Hospital, Capital Medical University, Beijing, China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, China
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6
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Li Q, Yu F, Song C, Zhao H, Xiao Q, Lao X, Yang S, Tang Y, Zhang F. HIV-1 Genotypic Resistance Testing Using Sanger and Next-Generation Sequencing in Adults with Low-Level Viremia in China. Infect Drug Resist 2022; 15:6711-6722. [PMID: 36438645 PMCID: PMC9697412 DOI: 10.2147/idr.s387215] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/27/2022] [Indexed: 08/08/2023] Open
Abstract
OBJECTIVE In this study, we aimed to determine drug-resistance mutations (DRMs) in HIV-1 patients with low-level viremia (LLV) and explored the performance of next-generation sequencing (NGS) in detecting HIV DRMs by using LLV samples. METHODS Overall, 80 samples with LLV were amplified and sequenced using a commercial Sanger sequencing (SS) genotyping kit. Furthermore, 51 samples successfully sequenced using SS were simultaneously subjected to NGS. Genotyping success rates of various viremia categories by two sequencing methods were calculated. Stanford HIV-1 drug-resistance database (HIVdb version 8.9) was used to analyze the DRMs. In the NGS assay, a threshold of 5% was considered for reporting low-frequency variants, and the DRMs detected using SS and NGS were compared. RESULTS The overall success rate of PR/RT regions was 88.1% (67/80) using SS and 86.3% (44/51) using NGS. Furthermore, a significant linear trend was noted between viral load and the genotyping success rate. A total of 38.8% (26/67) participants harbored at least one mutation, as revealed through SS. Moreover, the prevalence of DRMs in persistent LLV was significantly higher than that in intermittent LLV (62.1% vs. 21.1%; P < 0.05). A total of 69 DRMs were detected using the two sequencing methods at the threshold of 5%. Moreover, 10 DRMs missed by SS were detected using NGS, whereas 8 DRMs missed by NGS were detected by SS. CONCLUSION Our data suggested that the genotyping resistance testing is necessary to guide antiretroviral therapy optimization in LLV patients.
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Affiliation(s)
- Qun Li
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Fengting Yu
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Chuan Song
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, People’s Republic of China
| | - Hongxin Zhao
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Qing Xiao
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Xiaojie Lao
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Siyuan Yang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Yunxia Tang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Fujie Zhang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
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7
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Towards Next-Generation Sequencing for HIV-1 Drug Resistance Testing in a Clinical Setting. Viruses 2022; 14:v14102208. [PMID: 36298763 PMCID: PMC9608942 DOI: 10.3390/v14102208] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 09/25/2022] [Accepted: 10/05/2022] [Indexed: 11/15/2022] Open
Abstract
The HIV genotypic resistance test (GRT) is a standard of care for the clinical management of HIV/AIDS patients. In recent decades, population or Sanger sequencing has been the foundation for drug resistance monitoring in clinical settings. However, the advent of high-throughput or next-generation sequencing has caused a paradigm shift towards the detection and characterization of low-abundance covert mutations that would otherwise be missed by population sequencing. This is clinically significant, as these mutations can potentially compromise the efficacy of antiretroviral therapy, causing poor virologic suppression. Therefore, it is important to develop a more sensitive method so as to reliably detect clinically actionable drug-resistant mutations (DRMs). Here, we evaluated the diagnostic performance of a laboratory-developed, high-throughput, sequencing-based GRT using 103 archived clinical samples that were previously tested for drug resistance using population sequencing. As expected, high-throughput sequencing found all the DRMs that were detectable by population sequencing. Significantly, 78 additional DRMs were identified only by high-throughput sequencing, which is statistically significant based on McNemar's test. Overall, our results complement previous studies, supporting the notion that the two methods are well correlated, and the high-throughput sequencing method appears to be an excellent alternative for drug resistance testing in a clinical setting.
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Chen H, Hu J, Song C, Li M, Zhou Y, Dong A, Kang R, Hao J, Zhang J, Liu X, Li D, Feng Y, Liao L, Ruan Y, Xing H, Shao Y. Molecular transmission network of pretreatment drug resistance among human immunodeficiency virus-positive individuals and the impact of virological failure on those who received antiretroviral therapy in China. Front Med (Lausanne) 2022; 9:965836. [PMID: 36106325 PMCID: PMC9464856 DOI: 10.3389/fmed.2022.965836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 08/10/2022] [Indexed: 11/14/2022] Open
Abstract
Objectives We investigated the prevalence of pretreatment drug resistance (PDR), the molecular transmission network among HIV-positive individuals, and the impact of virological failure on those who received antiretroviral therapy (ART) in China. Methods Based on the World Health Organization (WHO) surveillance guidelines for PDR, a baseline survey and follow-up were conducted in 2018 and 2021, respectively. Demographic information and plasma samples were obtained from all participants. HIV pol gene region sequences were used to analyze the PDR and molecular transmission networks using the Stanford HIV database algorithm and HIV-TRACE, respectively. This study assessed the odds ratios (OR) of PDR to virological failure (viral load ≥ 50 copies/mL) after 3 years of ART using multivariable logistic regression. Results Of the 4,084 individuals, 370 (9.1%) had PDR. The prevalence of PDR to non-nucleoside reverse transcriptase inhibitors (5.2%) was notably higher than that to nucleoside reverse transcriptase inhibitors (0.7%, p < 0.001), protease inhibitors (3.0%, p < 0.001), and multidrug resistance (0.3%, p < 0.001). A total of 1,339 (32.8%) individuals from 361 clusters were enrolled in the molecular transmission network. Of the 361 clusters, 22 included two or more individuals with PDR. The prevalence of virological failure among HIV-positive individuals after 3 years of ART without PDR, those with PDR to Chinese listed drugs, and those with PDR to other drugs was 7.9, 14.3, and 12.6%, respectively. Compared with that in HIV-positive individuals without PDR, virological failure after 3 years of ART was significantly higher (OR: 2.02, 95% confidence interval (CI): 1.25–3.27) and not significantly different (OR: 1.72, 95% CI: 0.87–3.43) in individuals with PDR to Chinese listed drugs and those with PDR to other drugs, respectively. Missed doses in the past month were significantly associated with virological failure (OR, 2.82; 95% CI: 4.08–5.89). Conclusion The overall prevalence of PDR was close to a high level and had an impact on virological failure after 3 years of ART. Moreover, HIV drug-resistant strains were transmitted in the molecular transmission network. These results illustrate the importance of monitoring PDR and ensuring virological suppression through drug adherence.
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Current Research on HIV Drug Resistance—A Topical Collection with “Pathogens”. Pathogens 2022; 11:pathogens11090966. [PMID: 36145398 PMCID: PMC9504728 DOI: 10.3390/pathogens11090966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 08/22/2022] [Indexed: 11/17/2022] Open
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Maruapula D, Seatla KK, Morerinyane O, Molebatsi K, Giandhari J, de Oliveira T, Musonda RM, Leteane M, Mpoloka SW, Rowley CF, Moyo S, Gaseitsiwe S. Low-frequency HIV-1 drug resistance mutations in antiretroviral naïve individuals in Botswana. Medicine (Baltimore) 2022; 101:e29577. [PMID: 35838991 PMCID: PMC11132386 DOI: 10.1097/md.0000000000029577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 04/27/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Individuals living with human immunodeficiency virus (HIV) who experience virological failure (VF) after combination antiretroviral therapy (cART) initiation may have had low-frequency drug resistance mutations (DRMs) at cART initiation. There are no data on low-frequency DRMs among cART-naïve HIV-positive individuals in Botswana. METHODS We evaluated the prevalence of low-frequency DRMs among cART-naïve individuals previously sequenced using Sanger sequencing. The generated pol amplicons were sequenced by next-generation sequencing. RESULTS We observed low-frequency DRMs (detected at <20% in 33/103 (32%) of the successfully sequenced individuals, of whom four also had mutations detected at >20%. K65R was the most common low-frequency DRM detected in 8 individuals. Eighty-two of the 103 individuals had follow-up viral load data while on cART. Twenty-seven of the 82 individuals harbored low-frequency DRMs. Only 12 of 82 individuals experienced VF. The following low-frequency DRMs were observed in four individuals experiencing VF: K65R, K103N, V108I, and Y188C. No statistically significant difference was observed in the prevalence of low-frequency DRMs between individuals experiencing VF (4/12) and those not experiencing VF (23/70) (P = .97). However, individuals with non-nucleoside reverse transcriptase inhibitors-associated low-frequency DRMs were 2.68 times more likely to experience VF (odds ratio, 2.68; 95% confidential interval, 0.4-13.9) compared with those without (P = .22). CONCLUSION Next-generation sequencing was able to detect low-frequency DRMs in this cohort in Botswana, but these DRMs did not contribute significantly to VF.
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Affiliation(s)
- Dorcas Maruapula
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Kaelo K. Seatla
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- School of Allied Health Professions, University of Botswana, Gaborone, Botswana
| | | | - Kesaobaka Molebatsi
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Statistics, University of Botswana, Gaborone, Botswana
| | - Jennifer Giandhari
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Rosemary M. Musonda
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Melvin Leteane
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Sununguko W Mpoloka
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Christopher F. Rowley
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Sikhulile Moyo
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Simani Gaseitsiwe
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA
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Yu F, Li Q, Wang L, Zhao H, Wu H, Yang S, Tang Y, Xiao J, Zhang F. Drug Resistance to HIV-1 Integrase Inhibitors Among Treatment-Naive Patients in Beijing, China. Pharmgenomics Pers Med 2022; 15:195-203. [PMID: 35300056 PMCID: PMC8922317 DOI: 10.2147/pgpm.s345797] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 02/17/2022] [Indexed: 12/31/2022] Open
Abstract
Introduction Integrase strand transfer inhibitors (INSTIs) are important drugs that are currently used as the first line treatment for HIV-1 patients. The aim of this study was to characterize HIV-1 INSTI mutations among ART-naive patients in Beijing from 2019–2021. Methods 865 ART-naive patients were enrolled in this study between January 2019 and June 2021 in Beijing. The amplification of the entire pol gene containing the reverse transcriptase, protease and integrase regions was performed using a validated In-house SBS method. HIV-1 subtypes and circulating recombinant forms (CRFs) were determined using the COMET online tool (http://comet.retrovirology.lu). Stanford HIV-1 drug resistance database (HIVdb version 8.9) was used to analyze the mutations. Results 865 HIV-1 pol sequences were successfully amplified and sequenced. Among them, no major INSTI-related mutations were identified, but 12 polymorphic accessory mutations were found. Two patients have E138A and G163R mutations respectively and both could cause low-level resistance to RAL and EVG. Furthermore, one patient having S230R mutation resulted in low-level resistance to RAL, EVG, DTG and BIC. Conclusion The prevalence of INSTIs mutations remains low, which demonstrated that INSTIs have good applicability currently in our city. Nevertheless, it is very important to monitor the INSTI-related mutations in Beijing.
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Affiliation(s)
- Fengting Yu
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Qun Li
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Linghang Wang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Hongxin Zhao
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Hao Wu
- Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Siyuan Yang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Yunxia Tang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Jiang Xiao
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
| | - Fujie Zhang
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
- Clinical Center for HIV/AIDS, Capital Medical University, Beijing, People’s Republic of China
- Correspondence: Fujie Zhang, Clinical and Research Center of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of China, Tel +86 10 84322581, Email
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Xu X, Luo L, Song C, Li J, Chen H, Zhu Q, Lan G, Liang S, Shen Z, Cao Z, Feng Y, Liao L, Xing H, Shao Y, Ruan Y. Survey of pretreatment HIV drug resistance and the genetic transmission networks among HIV-positive individuals in southwestern China, 2014-2020. BMC Infect Dis 2021; 21:1153. [PMID: 34772365 PMCID: PMC8590229 DOI: 10.1186/s12879-021-06847-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 11/03/2021] [Indexed: 11/10/2022] Open
Abstract
Background Pretreatment drug resistance (PDR) can limit the effectiveness of HIV antiretroviral therapy (ART). The aim of this study was to assess the prevalence of PDR among HIV-positive individuals that initiated antiretroviral therapy in 2014–2020 in southwestern China. Methods Consecutive cross-sectional surveys were conducted in Qinzhou, Guangxi. We obtained blood samples from individuals who were newly diagnosed with HIV in 2014–2020. PDR and genetic networks analyses were performed by HIV-1 pol sequences using the Stanford HIV-database algorithm and HIV-TRACE, respectively. Univariate and multivariate logistic regression models were used to explore the potential factors associated with PDR. Results In total, 3236 eligible HIV-positive individuals were included. The overall prevalence of PDR was 6.0% (194/3236). The PDR frequency to NNRTI (3.3%) was much higher than that of NRTI (1.7%, p < 0.001) and PI (1.2%, p < 0.001). A multivariate logistic regression analysis revealed that PDR was significantly higher among individuals aged 18–29 (adjusted odds ratio (aOR): 1.79, 95% CI 1.28–2.50) or 30–49 (aOR: 2.82, 95% CI 1.73–4.82), and harboring CRF08_BC (aOR: 3.23, 95% CI 1.58–6.59). A total of 1429 (43.8%) sequences were linked forming transmission clusters ranging in size from 2 to 119 individuals. Twenty-two individuals in 10 clusters had the same drug resistant mutations (DRMs), mostly to NNRTIs (50%, 5/10). Conclusions The overall prevalence of PDR was medium, numerous cases of the same DRMs among genetically linked individuals in networks further illustrated the importance of surveillance studies for mitigating PDR. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06847-5.
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Affiliation(s)
- Xiaoshan Xu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Liuhong Luo
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, 530028, China
| | - Chang Song
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Jianjun Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, 530028, China
| | - Huanhuan Chen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, 530028, China
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, 530028, China
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, 530028, China
| | - Shujia Liang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, 530028, China
| | - Zhiyong Shen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, 530028, China
| | - Zhiqiang Cao
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yi Feng
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Lingjie Liao
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Hui Xing
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yiming Shao
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yuhua Ruan
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
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