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Ouyang F, Yuan D, Zhai W, Liu S, Zhou Y, Yang H. HIV-1 Drug Resistance Detected by Next-Generation Sequencing among ART-Naïve Individuals: A Systematic Review and Meta-Analysis. Viruses 2024; 16:239. [PMID: 38400015 PMCID: PMC10893194 DOI: 10.3390/v16020239] [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: 11/20/2023] [Revised: 12/31/2023] [Accepted: 01/30/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND There are an increasing number of articles focused on the prevalence and clinical impact of pretreatment HIV drug resistance (PDR) detected by Sanger sequencing (SGS). PDR may contribute to the increased likelihood of virologic failure and the emergence of new resistance mutations. As SGS is gradually replaced by next-generation sequencing (NGS), it is necessary to assess the levels of PDR using NGS in ART-naïve patients systematically. NGS can detect the viral variants (low-abundance drug-resistant HIV-1 variants (LA-DRVs)) of virus quasi-species at levels below 20% that SGS may fail to detect. NGS has the potential to optimize current HIV drug resistance surveillance methods and inform future research directions. As the NGS technique has high sensitivity, it is highly likely that the level of pretreatment resistance would be underestimated using conventional techniques. METHODS For the systematic review and meta-analysis, we searched for original studies published in PubMed, Web of Science, Scopus, and Embase before 30 March 2023 that focused exclusively on the application of NGS in the detection of HIV drug resistance. Pooled prevalence estimates were calculated using a random effects model using the 'meta' package in R (version 4.2.3). We described drug resistance detected at five thresholds (>1%, 2%, 5%, 10%, and 20% of virus quasi-species). Chi-squared tests were used to analyze differences between the overall prevalence of PDR reported by SGS and NGS. RESULTS A total of 39 eligible studies were selected. The studies included a total of 15,242 ART-naïve individuals living with HIV. The prevalence of PDR was inversely correlated with the mutation detection threshold. The overall prevalence of PDR was 29.74% at the 1% threshold, 22.43% at the 2% threshold, 15.47% at the 5% threshold, 12.95% at the 10% threshold, and 11.08% at the 20% threshold. The prevalence of PDR to INSTIs was 1.22% (95%CI: 0.58-2.57), which is the lowest among the values for all antiretroviral drugs. The prevalence of LA-DRVs was 9.45%. At the 2% and 20% detection threshold, the prevalence of PDR was 22.43% and 11.08%, respectively. Resistance to PIs and INSTIs increased 5.52-fold and 7.08-fold, respectively, in those with a PDR threshold of 2% compared with those with PDR at 20%. However, resistance to NRTIs and NNRTIs increased 2.50-fold and 2.37-fold, respectively. There was a significant difference between the 2% and 5% threshold for detecting HIV drug resistance. There was no statistically significant difference between the results reported by SGS and NGS when using the 20% threshold for reporting resistance mutations. CONCLUSION In this study, we found that next-generation sequencing facilitates a more sensitive detection of HIV-1 drug resistance than SGS. The high prevalence of PDR emphasizes the importance of baseline resistance and assessing the threshold for optimal clinical detection using NGS.
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Affiliation(s)
- Fei Ouyang
- Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China; (F.O.); (D.Y.); (W.Z.); (S.L.)
| | - Defu Yuan
- Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China; (F.O.); (D.Y.); (W.Z.); (S.L.)
| | - Wenjing Zhai
- Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China; (F.O.); (D.Y.); (W.Z.); (S.L.)
| | - Shanshan Liu
- Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China; (F.O.); (D.Y.); (W.Z.); (S.L.)
| | - Ying Zhou
- Department of HIV/STD Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Haitao Yang
- Key Laboratory of Environmental Medicine Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing 210009, China; (F.O.); (D.Y.); (W.Z.); (S.L.)
- Jiangsu Health Development Research Center, Nanjing 210029, China
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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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Kiros M, Biset S, Gebremariam B, Yalew GT, Abegaz WE, Geteneh A. Trends in HIV-1 pretreatment drug resistance and HIV-1 variant dynamics among antiretroviral therapy-naive Ethiopians from 2003 to 2018: a pooled sequence analysis. Virol J 2023; 20:243. [PMID: 37880705 PMCID: PMC10601210 DOI: 10.1186/s12985-023-02205-w] [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: 05/29/2023] [Accepted: 10/04/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND Ethiopia is among the highly HIV-affected countries, with reported 12,000 and 12,000 AIDS-related deaths and incidents as per reports from 2021. Although the country has made a promising progress in antiretroviral therapy, recent studies have indicated that pretreatment drug resistance (PDR) is alarmingly increasing, which has become a challenge for the effectiveness of HIV treatment. Epidemiologic data on PDR is necessary to help establish ART regimens with good efficacy. Thus, this systematic review aimed to determine the trend analysis of PDR among ART-naïve individuals along with HIV variant dynamics in Ethiopia. METHOD HIV-1 pol sequences from studies conducted between 2003 and 2018 among ART-naïve Ethiopian individuals were retrieved from GenBank and analyzed for the presence of PDR mutations (PDRM) along with the analysis of HIV-1 variant dynamics. The Calibrated Population Resistance (CPR) tool Version 8.1 and the REGA HIV-1 Subtyping Tool Version 3 were used to determine the PDRM and HIV-1 genetic diversity, respectively. RESULT We identified nine studies and analyzed 1070 retrieved HIV-1 pol sequences in this systematic review. The pooled prevalence of PDR was 4.8% (51/1070), including 1.4% (15/1070), 2.8% (30/1070), and 0.8% (9/1070) for nucleoside reverse transcriptase inhibitor (NRTI), non-NRTI (NNRTI), and protease inhibitor (PI) resistance, respectively. NRTI and NNRTI concurrent PDRM were observed among 0.2% (2/799) of the analyzed sequences. The overall PDR prevalence has been increasing over the years. Though the prevalence of the NNRTI, NRTI, and PI PDR also increased over the years, the NNRTI increment was more pronounced than the others, reaching 7.84% in 2018 from 2.19% in 2003. The majority (97%; 1038/1070) of the genetic diversity was HIV-1 subtype C virus, followed by subtype C' (2%; 20/1038) and other subtypes (1%; 10/1038). CONCLUSIONS According to this systematic review, the overall pooled prevalence of PDR is low. Despite the low prevalence, there has been an increasing trend of PDR over the years, which implies the need for routine surveillance of PDRMs along with preventive measures. Hence, this supports the recently endorsed transition of ART regimens from NNRTI to integrase strand transfer inhibitor-based regimens recommended by the WHO. In addition, this finding underscores the need for routine baseline genotypic drug resistance testing for all newly diagnosed HIV-infected patients before initiating treatment to halt the upward trend of PDR.
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Affiliation(s)
- Mulugeta Kiros
- Department of Medical Laboratory Science, CollegeofMedicineandHealth Sciences, Aksum University, Aksum, Ethiopia.
| | - Sirak Biset
- Department of Medical Microbiology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
| | - Birhane Gebremariam
- Department of Medical Laboratory Science, CollegeofMedicineandHealth Sciences, Aksum University, Aksum, Ethiopia
| | - Gebrehiwet Tesfay Yalew
- Department of Medical Laboratory Science, College of Medicine and Health Sciences, Adigrat University, Adigrat, Ethiopia
| | - Woldaregay Erku Abegaz
- Department of Microbiology, Parasitology, and Immunology, School of Medicine, Addis Ababa University, Addis Ababa, Ethiopia
| | - Alene Geteneh
- Department of Medical Laboratory Sciences, College of Health Sciences, Woldia University, Woldia, Ethiopia
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Hong H, Tang C, Liu Y, Jiang H, Fang T, Xu G. HIV-1 drug resistance and genetic transmission network among newly diagnosed people living with HIV/AIDS in Ningbo, China between 2018 and 2021. Virol J 2023; 20:233. [PMID: 37833806 PMCID: PMC10576354 DOI: 10.1186/s12985-023-02193-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND As the HIV epidemic continues to grow, transmitted drug resistance(TDR) and determining relationship of HIV transmission are major barriers to reduce the risk of HIV transmissions.This study aimed to examine the molecular epidemiology and TDR and evaluated the transmission pattern among newly diagnosed people living with HIV/AIDS(PLWHA) in Ningbo city, which could contribute to the development of targeted precision interventions. METHODS Consecutive cross-sectional surveys were conducted in Ningbo City between January 2018 and December 2021. The HIV-1 pol gene region was amplified and sequenced for drug resistance and genetic transmission network analysis. TDR was determined using the Stanford University HIV Drug Resistance Database. Genetic transmission network was visualized using Cytoscape with the genetic distance threshold of 0.013. RESULTS A total of 1006 sequences were sequenced successfully, of which 61 (6.1%) showed evidence of TDR. The most common mutations were K103N (2.3%), E138A/G/Q (1.7%) and V179D/E (1.2%). 12 HIV-1 genotypes were identified, with CRF07_BC being the major genotype (43.3%, 332/767), followed by CRF01_AE (33.7%, 339/1006). 444 (44.1%) pol sequences formed 856 links within 120 transmission clusters in the network. An increasing trend in clustering rate between 2018 and 2021(χ2 = 9.546, P = 0.023) was observed. The odds of older age (≥ 60 years:OR = 2.038, 95%CI = 1.072 ~ 3.872, compared to < 25 years), HIV-1 genotypes (CRF07_BC: OR = 2.147, 95%CI = 1.582 ~ 2.914; CRF55_01B:OR = 2.217, 95%CI = 1.201 ~ 4.091, compared to CRF01_AE) were significantly related to clustering. Compared with CRF01_AE, CRF07_BC were prone to form larger clusters. The largest cluster with CRF07_BC was increased from 15 cases in 2018 to 83 cases in 2021. CONCLUSIONS This study revealed distribution of HIV-1 genotypes, and genetic transmission network were diverse and complex in Ningbo city. The prevalence of TDR was moderate, and NVP and EFV were high-level NNRTI resistance. Individuals aged ≥ 60 years old were more easily detected in the networks and CRF07_BC were prone to form rapid growth and larger clusters. These date suggested that surveillance and comprehensive intervention should be designed for key rapid growth clusters to reduce the potential risk factors of HIV-1 transmission.
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Affiliation(s)
- Hang Hong
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China
| | - Chunlan Tang
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China
| | - Yuhui Liu
- Ningbo Center for Disease Control and Prevention, Ningbo, Zhengjiang, 315010, China
| | - Haibo Jiang
- Ningbo Center for Disease Control and Prevention, Ningbo, Zhengjiang, 315010, China
| | - Ting Fang
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China
| | - Guozhang Xu
- School of Public health, Health Science Center, Ningbo University, Ningbo, Zhengjiang, 315211, China.
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Deng X, Liang Z, Cai W, Li F, Li J, Hu F, Lan Y. Transmission networks of hepatitis C virus among HIV/HCV-coinfected patients in Guangdong, China. Virol J 2022; 19:117. [PMID: 35836270 PMCID: PMC9284750 DOI: 10.1186/s12985-022-01849-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 07/01/2022] [Indexed: 11/18/2022] Open
Abstract
Background Coinfection with hepatitis C virus (HCV) is common in human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) patients due to shared routes of transmission. We aimed to investigate the characteristics of HCV subgenotypes among HIV/HCV-coinfected patients in Guangdong and explore the molecular transmission networks and related risk factors for HCV strains. Methods Plasma samples were obtained from 356 HIV/HCV-coinfected patients for HCV NS5B region sequencing. A neighbor-joining phylogenetic tree was constructed to affirm HCV subgenotypes. The transmission networks based on maximum likelihood phylogenetic tree were determined by Cluster Picker, and visualized using Cytoscape 3.2.1. Results A total of 302 HCV NS5B sequences were successfully amplified and sequenced from the 356 plasma samples. A neighbor-joining phylogenetic tree based on the 302 NS5B sequences revealed the profile of HCV subgenotypes circulating among HIV/HCV coinfection patients in Guangdong. Two predominant strains were found to be 6a (58.28%, 176/302) and 1b (18.54%, 56/302), followed by 3a (10.93%, 33/302), 3b (6.95%, 21/302), 1a (3.64%, 11/302), 2a (0.99%, 3/302) and 6n (0.66%, 2/302). A molecular transmission network of five major HCV genotypes was constructed, with a clustering rate of 44.04%. The clustering rates of subgenotypes 1a, 3a, 3b, 1b, and 6a were 18.18% (2/11), 42.42%, 52.38%, 48.21%, and 44.89%, respectively. Multivariate logistic regression analysis showed no significant effects from sex, age, transmission route, geographical region, baseline CD4 + T cell count or subgenotype (P > 0.05), except marital status. Married or cohabiting people (compared with unmarried people) had more difficulty forming transmission networks. Conclusions In summary, this study, based on HCV NS5B subgenotypes, revealed the HCV subtype diversity and distribution among HIV/HCV-coinfected patients in Guangdong. Marital status inclined to be the factor influencing HCV transmission networks formation.
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Affiliation(s)
- Xizi Deng
- Infectious Diseases Institute, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China
| | - Zhiwei Liang
- Infectious Diseases Institute, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China
| | - Weiping Cai
- Infectious Diseases Institute, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China
| | - Feng Li
- Infectious Diseases Institute, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China
| | - Junbin Li
- Infectious Diseases Institute, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China
| | - Fengyu Hu
- Infectious Diseases Institute, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China.
| | - Yun Lan
- Infectious Diseases Institute, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China.
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Kirichenko A, Kireev D, Lopatukhin A, Murzakova A, Lapovok I, Saleeva D, Ladnaya N, Gadirova A, Ibrahimova S, Safarova A, Grigoryan T, Petrosyan A, Sarhatyan T, Gasich E, Bunas A, Glinskaya I, Yurovsky P, Nurov R, Soliev A, Ismatova L, Musabaev E, Kazakova E, Rakhimova V, Pokrovsky V. Prevalence of HIV-1 drug resistance in Eastern European and Central Asian countries. PLoS One 2022; 17:e0257731. [PMID: 35061671 PMCID: PMC8782385 DOI: 10.1371/journal.pone.0257731] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 09/08/2021] [Indexed: 11/18/2022] Open
Abstract
Background Eastern Europe and Central Asia (EECA) is one of the regions where the HIV epidemic continues to grow at a concerning rate. Antiretroviral therapy (ART) coverage in EECA countries has significantly increased during the last decade, which can lead to an increase in the risk of emergence, transmission, and spread of HIV variants with drug resistance (DR) that cannot be controlled. Because HIV genotyping cannot be performed in these countries, data about HIV DR are limited or unavailable. Objectives To monitor circulating HIV-1 genetic variants, assess the prevalence of HIV DR among patients starting antiretroviral therapy, and reveal potential transmission clusters among patients in six EECA countries: Armenia, Azerbaijan, Belarus, Russia, Tajikistan, and Uzbekistan. Materials and methods We analyzed 1071 HIV-1 pol-gene fragment sequences (2253–3369 bp) from patients who were initiating or reinitiating first-line ART in six EECA counties, i.e., Armenia (n = 120), Azerbaijan (n = 96), Belarus (n = 158), Russia (n = 465), Tajikistan (n = 54), and Uzbekistan (n = 178), between 2017 and 2019. HIV Pretreatment DR (PDR) and drug resistance mutation (DRM) prevalence was estimated using the Stanford HIV Resistance Database. The PDR level was interpreted according to the WHO standard PDR survey protocols. HIV-1 subtypes were determined using the Stanford HIV Resistance Database and subsequently confirmed by phylogenetic analysis. Transmission clusters were determined using Cluster Picker. Results Analyses of HIV subtypes showed that EECA, in general, has the same HIV genetic variants of sub-subtype A6, CRF63_02A1, and subtype B, with different frequencies and representation for each country. The prevalence of PDR to any drug class was 2.8% in Uzbekistan, 4.2% in Azerbaijan, 4.5% in Russia, 9.2% in Armenia, 13.9% in Belarus, and 16.7% in Tajikistan. PDR to protease inhibitors (PIs) was not detected in any country. PDR to nucleoside reverse-transcriptase inhibitors (NRTIs) was not detected among patients in Azerbaijan, and was relatively low in other countries, with the highest prevalence in Tajikistan (5.6%). The prevalence of PDR to nonnucleoside reverse-transcriptase inhibitors (NNRTIs) was the lowest in Uzbekistan (2.8%) and reached 11.1% and 11.4% in Tajikistan and Belarus, respectively. Genetic transmission network analyses identified 226/1071 (21.1%) linked individuals, forming 93 transmission clusters mainly containing two or three sequences. We found that the time since HIV diagnosis in clustered patients was significantly shorter than that in unclustered patients (1.26 years vs 2.74 years). Additionally, the K103N/S mutation was mainly observed in clustered sequences (6.2% vs 2.8%). Conclusions Our study demonstrated different PDR prevalence rates and DR dynamics in six EECA countries, with worrying levels of PDR in Tajikistan and Belarus, where prevalence exceeded the 10% threshold recommended by the WHO for immediate public health action. Because DR testing for clinical purposes is not common in EECA, it is currently extremely important to conduct surveillance of HIV DR in EECA due to the increased ART coverage in this region.
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Affiliation(s)
- Alina Kirichenko
- Central Research Institute of Epidemiology, Moscow, Russian Federation
- * E-mail:
| | - Dmitry Kireev
- Central Research Institute of Epidemiology, Moscow, Russian Federation
| | - Alexey Lopatukhin
- Central Research Institute of Epidemiology, Moscow, Russian Federation
| | | | - Ilya Lapovok
- Central Research Institute of Epidemiology, Moscow, Russian Federation
| | - Daria Saleeva
- Central Research Institute of Epidemiology, Moscow, Russian Federation
| | - Natalya Ladnaya
- Central Research Institute of Epidemiology, Moscow, Russian Federation
| | | | | | - Aygun Safarova
- Republic Center of the Struggle against AIDS, Baku, Azerbaijan
| | | | | | | | - Elena Gasich
- Republican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus
| | - Anastasia Bunas
- Republican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus
| | - Iryna Glinskaya
- Republican Center for Hygiene, Epidemiology and Public Health, Minsk, Belarus
| | - Pavel Yurovsky
- Republican Center for Hygiene, Epidemiology and Public Health, Minsk, Belarus
| | - Rustam Nurov
- Republican AIDS prevention center, Dushanbe, Tajikistan
| | - Alijon Soliev
- Republican AIDS prevention center, Dushanbe, Tajikistan
| | | | | | | | - Visola Rakhimova
- Center for development of profession qualification of medical workers, Tashkent, Uzbekistan
| | - Vadim Pokrovsky
- Central Research Institute of Epidemiology, Moscow, Russian Federation
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García-Morales C, Tapia-Trejo D, Matías-Florentino M, Quiroz-Morales VS, Dávila-Conn V, Beristain-Barreda Á, Cárdenas-Sandoval M, Becerril-Rodríguez M, Iracheta-Hernández P, Macías-González I, García-Mendiola R, Guzmán-Carmona A, Zarza-Sánchez E, Cruz RA, González-Rodríguez A, Reyes-Terán G, Ávila-Ríos S. HIV Pretreatment Drug Resistance Trends in Mexico City, 2017-2020. Pathogens 2021; 10:1587. [PMID: 34959542 PMCID: PMC8708254 DOI: 10.3390/pathogens10121587] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 11/25/2021] [Accepted: 11/30/2021] [Indexed: 11/19/2022] Open
Abstract
In response to increasing pretreatment drug resistance (PDR), Mexico changed its national antiretroviral treatment (ART) policy, recommending and procuring second-generation integrase strand-transfer inhibitor (INSTI)-based regimens as preferred first-line options since 2019. We present a four-year observational study describing PDR trends across 2017-2020 at the largest HIV diagnosis and primary care center in Mexico City. A total of 6688 baseline protease-reverse transcriptase and 6709 integrase sequences were included. PDR to any drug class was 14.4% (95% CI, 13.6-15.3%). A significant increasing trend for efavirenz/nevirapine PDR was observed (10.3 to 13.6%, p = 0.02). No increase in PDR to second-generation INSTI was observed, remaining under 0.3% across the study period. PDR was strongly associated with prior exposure to ART (aOR: 2.9, 95% CI: 1.9-4.6, p < 0.0001). MSM had higher odds of PDR to efavirenz/nevirapine (aOR: 2.0, 95% CI: 1.0-3.7, p = 0.04), reflecting ongoing transmission of mutations such as K103NS and E138A. ART restarters showed higher representation of cisgender women and injectable drug users, higher age, and lower education level. PDR to dolutegravir/bictegravir remained low in Mexico City, although further surveillance is warranted given the short time of ART optimization. Our study identifies demographic characteristics of groups with higher risk of PDR and lost to follow-up, which may be useful to design differentiated interventions locally.
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Affiliation(s)
- Claudia García-Morales
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Daniela Tapia-Trejo
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Margarita Matías-Florentino
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Verónica Sonia Quiroz-Morales
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Vanessa Dávila-Conn
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Ángeles Beristain-Barreda
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Miroslava Cárdenas-Sandoval
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Manuel Becerril-Rodríguez
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Patricia Iracheta-Hernández
- Condesa Specialised Clinic, General Benjamín Hill 24, Colonia Condesa, Mexico City 06140, Mexico; (P.I.-H.); (I.M.-G.); (A.G.-R.)
| | - Israel Macías-González
- Condesa Specialised Clinic, General Benjamín Hill 24, Colonia Condesa, Mexico City 06140, Mexico; (P.I.-H.); (I.M.-G.); (A.G.-R.)
| | - Rebecca García-Mendiola
- Condesa Iztapalapa Specialised Clinic, Combate de Celaya s/n, Colonia Unidad Habitacional Vicente Guerrero, Mexico City 09730, Mexico; (R.G.-M.); (A.G.-C.); (R.A.C.)
| | - Alejandro Guzmán-Carmona
- Condesa Iztapalapa Specialised Clinic, Combate de Celaya s/n, Colonia Unidad Habitacional Vicente Guerrero, Mexico City 09730, Mexico; (R.G.-M.); (A.G.-C.); (R.A.C.)
| | - Eduardo Zarza-Sánchez
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
| | - Raúl Adrián Cruz
- Condesa Iztapalapa Specialised Clinic, Combate de Celaya s/n, Colonia Unidad Habitacional Vicente Guerrero, Mexico City 09730, Mexico; (R.G.-M.); (A.G.-C.); (R.A.C.)
| | - Andrea González-Rodríguez
- Condesa Specialised Clinic, General Benjamín Hill 24, Colonia Condesa, Mexico City 06140, Mexico; (P.I.-H.); (I.M.-G.); (A.G.-R.)
| | - Gustavo Reyes-Terán
- Coordinating Commission of the National Institutes of Health and High Specialty Hospitals, Periférico Sur 4809, Colonia Arenal de Tepepan, Mexico City 14610, Mexico;
| | - Santiago Ávila-Ríos
- Centre for Research in Infectious Diseases, National Institute of Respiratory Diseases, Calzada de Tlalpan 4502, Colonia Sección XVI, Mexico City 14080, Mexico; (C.G.-M.); (D.T.-T.); (M.M.-F.); (V.S.Q.-M.); (V.D.-C.); (Á.B.-B.); (M.C.-S.); (M.B.-R.); (E.Z.-S.)
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Dávila‐Conn V, García‐Morales C, Matías‐Florentino M, López‐Ortiz E, Paz‐Juárez HE, Beristain‐Barreda Á, Cárdenas‐Sandoval M, Tapia‐Trejo D, López‐Sánchez DM, Becerril‐Rodríguez M, García‐Esparza P, Macías‐González I, Iracheta‐Hernández P, Weaver S, Wertheim JO, Reyes‐Terán G, González‐Rodríguez A, Ávila‐Ríos S. Characteristics and growth of the genetic HIV transmission network of Mexico City during 2020. J Int AIDS Soc 2021; 24:e25836. [PMID: 34762774 PMCID: PMC8583431 DOI: 10.1002/jia2.25836] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 10/13/2021] [Indexed: 12/04/2022] Open
Abstract
INTRODUCTION Molecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention. METHODS All new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV-TRACE tool: Seguro HIV-TRACE. Socio-demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions. RESULTS A total of 3168 HIV sequences from unique individuals were included. One thousand and one-hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p<0.001; >34 vs. <24 years), being a man who has sex with men (MSM) (aOR: 2.47, p = 0.004; MSM vs. cisgender women), having higher viral load (aOR: 1.28, p<0.001) and higher CD4+ T cell count (aOR: 1.80, p<0.001; ≥500 vs. <200 cells/mm3 ) remained associated with higher odds of clustering. Compared to MSM, cisgender women and heterosexual men had significantly lower education (none or any elementary: 59.1% and 54.2% vs. 16.6%, p<0.001) and socio-economic status (low income: 36.4% and 29.0% vs. 18.6%, p = 0.03) than MSM. We identified 10 (2.6%) clusters with constant growth, for prioritized intervention, that included intersecting sexual risk groups, highly connected nodes and bridge nodes between possible sub-clusters with high growth potential. CONCLUSIONS HIV transmission in Mexico City is strongly driven by young MSM with higher education level and recent infection. Nevertheless, leveraging network inference, we identified actively growing clusters that could be prioritized for focused intervention with demographic and risk characteristics that do not necessarily reflect the ones observed in the overall clustering population. Further studies evaluating different models to predict growing clusters are warranted. Focused interventions will have to consider structural and risk disparities between the MSM and the heterosexual populations.
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Affiliation(s)
- Vanessa Dávila‐Conn
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Claudia García‐Morales
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | | | - Eduardo López‐Ortiz
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Héctor E. Paz‐Juárez
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Ángeles Beristain‐Barreda
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | | | - Daniela Tapia‐Trejo
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Dulce M. López‐Sánchez
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Manuel Becerril‐Rodríguez
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Pedro García‐Esparza
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | | | | | - Steven Weaver
- Institute for Genomics and Evolutionary MedicineTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Joel O. Wertheim
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Gustavo Reyes‐Terán
- Coordinating Commission of the National Institutes of Health and High Specialty HospitalsMexico CityMexico
| | | | - Santiago Ávila‐Ríos
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
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Near point-of-care, point-mutation test to detect drug resistance in HIV-1: a validation study in a Mexican cohort. AIDS 2020; 34:1331-1338. [PMID: 32205723 DOI: 10.1097/qad.0000000000002524] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Pretreatment HIV-drug resistance (PDR, HIVDR) to non-nucleoside reverse transcriptase inhibitors (NNRTIs) is increasing globally. NNRTIs continue to be used as first-line antiretroviral therapy (ART) in some communities due to the cost of dolutegravir-based ART or dolutegravir-associated adverse events. A simplified version of the oligonucleotide ligation assay (OLA) - 'OLA-Simple' - is a low-cost, near point-of-care assay that provides ready-to-use lyophilized reagents and reports HIVDR mutations as colored lines on lateral flow strips. Our objective was to design and validate OLA-Simple for a Mexican cohort. DESIGN OLA-Simple probes to detect K65R, K103N/S, Y181C, M184V, and G190A were optimized for HIV Mexican sequences. Sixty clinical plasma specimens were analyzed by OLA-Simple by technicians blinded to Illumina-MiSeq sequences, and HIVDR results were compared. METHODS Plasma RNA was tested using OLA-Simple kits. OLA-Simple lateral flow strips were read by in-house software, and were classified as mutant or wild-type at each codon. The comparison of results by OLA-Simple and Miseq was used to generate receiver-operating characteristic curves. RESULTS OLA-Simple PCR amplified 59 of 60 specimens and successfully genotyped 287 of 295 codons, with eight of 295 (2.7%) indeterminate results. Compared to MiSeq, OLA-Simple gave five of 295 (1.7%) false-positive and four of 295 (1.4%) false-negative results. Excluding indeterminate results, OLA-Simple classified mutant with an accuracy of 97.4 and 98.8% when using thresholds at 10 and 25% mutant within an individual's HIV quasispecies, respectively. CONCLUSIONS Compared to MiSeq, OLA-Simple detected HIVDR with high sensitivity and accuracy. OLA-Simple could expand access to affordable and rapid HIVDR testing to guide appropriate ART choices in populations using NNRTI-based ART.
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