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Christensen KT, Pierard F, Bonsall D, Bowden R, Barnes E, Florence E, Ansari MA, Nguyen D, de Cesare M, Nevens F, Robaeys G, Schrooten Y, Busschots D, Simmonds P, Vandamme AM, Van Wijngaerden E, Dierckx T, Cuypers L, Van Laethem K. Phylogenetic Analysis of Hepatitis C Virus Infections in a Large Belgian Cohort Using Next-Generation Sequencing of Full-Length Genomes. Viruses 2023; 15:2391. [PMID: 38140632 PMCID: PMC10747466 DOI: 10.3390/v15122391] [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: 09/04/2023] [Revised: 09/25/2023] [Accepted: 09/26/2023] [Indexed: 12/24/2023] Open
Abstract
The hepatitis C virus (HCV) epidemic in Western countries is primarily perpetuated by the sub-populations of men who have sex with men (MSM) and people who inject drugs (PWID). Understanding the dynamics of transmission in these communities is crucial for removing the remaining hurdles towards HCV elimination. We sequenced 269 annotated HCV plasma samples using probe enrichment and next-generation sequencing, obtaining 224 open reading frames of HCV (OR497849-OR498072). Maximum likelihood phylogenies were generated on the four most prevalent subtypes in this study (HCV1a, 1b, 3a, 4d) with a subsequent transmission cluster analysis. The highest rate of clustering was observed for HCV4d samples (13/17 (76.47%)). The second highest rate of clustering was observed in HCV1a samples (42/78 (53.85%)) with significant association with HIV-positive MSM. HCV1b and HCV3a had very low rates of clustering (2/83 (2.41%) and (0/29)). The spread of the prevalent subtype HCV1b appears to have been largely curtailed, and we demonstrate the onwards transmission of HCV1a and HCV4d in the HIV-positive MSM population across municipal borders. More systematic data collection and sequencing is needed to allow a better understanding of the HCV transmission among the community of PWID and overcome the remaining barriers for HCV elimination in Belgium.
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Affiliation(s)
- Kasper T. Christensen
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (F.P.); (Y.S.); (A.-M.V.); (T.D.); (L.C.); (K.V.L.)
| | - Florian Pierard
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (F.P.); (Y.S.); (A.-M.V.); (T.D.); (L.C.); (K.V.L.)
| | - David Bonsall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK;
- The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; (R.B.); (D.N.); (M.d.C.)
| | - Rory Bowden
- The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; (R.B.); (D.N.); (M.d.C.)
| | - Eleanor Barnes
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford OX1 3SY, UK;
- Translational Gastroenterology Unit, University of Oxford, Oxford OX3 9DU, UK
- Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford OX3 9DU, UK
| | - Eric Florence
- Department of General Internal Medicine, Infectious Diseases and Tropical Medicine, Antwerp University Hospital, 2650 Edegem, Belgium;
- Department of Clinical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium
| | - M. Azim Ansari
- Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK;
| | - Dung Nguyen
- The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; (R.B.); (D.N.); (M.d.C.)
| | - Mariateresa de Cesare
- The Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; (R.B.); (D.N.); (M.d.C.)
| | - Frederik Nevens
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, 3000 Leuven, Belgium; (F.N.); (G.R.)
| | - Geert Robaeys
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, 3000 Leuven, Belgium; (F.N.); (G.R.)
- Faculty of Medicine and Life Sciences—LCRC, UHasselt, Agoralaan, 3590 Diepenbeek, Belgium;
- Department of Gastroenterology and Hepatology, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium
| | - Yoeri Schrooten
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (F.P.); (Y.S.); (A.-M.V.); (T.D.); (L.C.); (K.V.L.)
- Department of Laboratory Medicine, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Dana Busschots
- Faculty of Medicine and Life Sciences—LCRC, UHasselt, Agoralaan, 3590 Diepenbeek, Belgium;
- Department of Gastroenterology and Hepatology, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium
| | - Peter Simmonds
- Henry Wellcome Building for Molecular Physiology, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Headington, Oxford OX3 7BN, UK;
| | - Anne-Mieke Vandamme
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (F.P.); (Y.S.); (A.-M.V.); (T.D.); (L.C.); (K.V.L.)
- Global Health and Tropical Medicine, Institute of Hygiene and Tropical Medicine, Universidade Nova de Lisboa, Rua da Junqueira 100, 1349-008 Lisbon, Portugal
| | - Eric Van Wijngaerden
- Department of General Internal Medicine, University Hospitals Leuven, 3000 Leuven, Belgium;
| | - Tim Dierckx
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (F.P.); (Y.S.); (A.-M.V.); (T.D.); (L.C.); (K.V.L.)
| | - Lize Cuypers
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (F.P.); (Y.S.); (A.-M.V.); (T.D.); (L.C.); (K.V.L.)
- Department of Laboratory Medicine, University Hospitals Leuven, 3000 Leuven, Belgium
- Laboratory of Clinical Microbiology, Department of Microbiology, Immunology and Transplantation, KU Leuven, 3000 Leuven, Belgium
| | - Kristel Van Laethem
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (F.P.); (Y.S.); (A.-M.V.); (T.D.); (L.C.); (K.V.L.)
- Department of Laboratory Medicine, University Hospitals Leuven, 3000 Leuven, Belgium
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Chao E, Chato C, Vender R, Olabode AS, Ferreira RC, Poon AFY. Molecular source attribution. PLoS Comput Biol 2022; 18:e1010649. [PMID: 36395093 PMCID: PMC9671344 DOI: 10.1371/journal.pcbi.1010649] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Elisa Chao
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Connor Chato
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Reid Vender
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
- School of Medicine, Queen’s University, Kingston, Ontario, Canada
| | - Abayomi S. Olabode
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Roux-Cil Ferreira
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Art F. Y. Poon
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
- * E-mail:
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Bartlett SR, Verich A, Carson J, Hosseini‐Hooshyar S, Read P, Baker D, Post JJ, Finlayson R, Bloch M, Doyle JS, Shaw D, Hellard M, Martinez M, Marks P, Dore GJ, Matthews GV, Applegate T, Martinello M. Patterns and correlates of hepatitis C virus phylogenetic clustering among people living with HIV in Australia in the direct‐acting antiviral era: A molecular epidemiology study among participants in the CEASE cohort. Health Sci Rep 2022; 5:e719. [PMID: 36000082 PMCID: PMC9388196 DOI: 10.1002/hsr2.719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 06/15/2022] [Accepted: 06/19/2022] [Indexed: 12/02/2022] Open
Abstract
Background and Aims In moving towards the elimination of hepatitis C virus (HCV) infection among people living with HIV, understanding HCV transmission patterns may provide insights to guide and evaluate interventions. In this study, we evaluated patterns of, and factors associated with HCV phylogenetic clustering among people living with HIV/HCV co‐infection in Australia in the direct‐acting antiviral era. Methods HCV RNA was extracted from dried blood spot (DBS) samples collected between 2014 and 2018 in the CEASE cohort study. The HCV Core‐E2 region was amplified by a polymerase chain reaction and Sanger sequenced. Maximum likelihood phylogenetic trees (1000 bootstrap replicates) were used to identify patterns of clustering (3% genetic distance threshold). Mixed‐effects logistic regression was used to determine correlates of phylogenetic clustering. Factors assessed were sexual risk behavior, education, injecting drug use, housing, employment, HIV viral load, age, sex, and sexuality. Results Phylogenetic trees were reconstructed for HCV subtype 1a (n = 139) and 3a (n = 63) sequences, with 29% (58/202) in a pair or cluster. Overall (n = 202), phylogenetic clustering was positively associated with younger age (under 40; adjusted odds ratio [aOR] 2.52, 95% confidence interval [CI] 1.20–5.29), and among gay and bisexual men (n = 168), was positively associated with younger age (aOR 2.61, 95% CI 1.10–6.19), higher education (aOR 2.58, 95% CI 1.09–6.13), and reporting high‐risk sexual behavior (aOR 3.94, 95% CI 1.31–11.84). During follow‐up, five reinfections were observed, but none were in phylogenetic clusters. Conclusion This study found a high proportion of phylogenetic relatedness, predominantly among younger people and gay and bisexual men reporting high‐risk sexual behavior. Despite this, few reinfections were observed, and reinfections demonstrated little relationship with known clusters. These findings highlight the importance of rapid HCV treatment initiation, together with monitoring of the phylogeny.
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Affiliation(s)
- Sofia R. Bartlett
- British Columbia Centre for Disease Control Vancouver British Columbia Canada
- School of Population and Public Health University of British Columbia Vancouver British Columbia Canada
| | - Andrey Verich
- The Kirby Institute, UNSW Sydney Sydney New South Wales Australia
| | - Joanne Carson
- The Kirby Institute, UNSW Sydney Sydney New South Wales Australia
| | | | - Phillip Read
- Kirketon Road Centre Sydney New South Wales Australia
| | - David Baker
- East Sydney Doctors Sydney New South Wales Australia
| | - Jeffrey J. Post
- The Albion Centre Sydney New South Wales Australia
- Department of Infectious Diseases Prince of Wales Hospital Sydney New South Wales Australia
- Prince of Wales Clinical School University of New South Wales Sydney Sydney New South Wales Australia
| | | | - Mark Bloch
- Holdsworth House Medical Practice Sydney New South Wales Australia
| | - Joseph S. Doyle
- Department of Infectious Diseases Alfred Health & Monash University Melbourne Victoria Australia
- Burnet Institute, Melbourne Victoria Australia
| | - David Shaw
- Royal Adelaide Hospital Adelaide South Australia Australia
| | - Margaret Hellard
- Department of Infectious Diseases Alfred Health & Monash University Melbourne Victoria Australia
- Burnet Institute, Melbourne Victoria Australia
| | - Maria Martinez
- The Kirby Institute, UNSW Sydney Sydney New South Wales Australia
| | - Philippa Marks
- The Kirby Institute, UNSW Sydney Sydney New South Wales Australia
| | - Gregory J. Dore
- The Kirby Institute, UNSW Sydney Sydney New South Wales Australia
- St Vincent's Hospital Sydney New South Wales Australia
| | - Gail V. Matthews
- The Kirby Institute, UNSW Sydney Sydney New South Wales Australia
- St Vincent's Hospital Sydney New South Wales Australia
| | - Tanya Applegate
- The Kirby Institute, UNSW Sydney Sydney New South Wales Australia
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Molecular Epidemiology and Baseline Resistance of Hepatitis C Virus to Direct Acting Antivirals in Croatia. Pathogens 2022; 11:pathogens11070808. [PMID: 35890052 PMCID: PMC9323280 DOI: 10.3390/pathogens11070808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/15/2022] [Accepted: 07/18/2022] [Indexed: 02/04/2023] Open
Abstract
Molecular epidemiology of hepatitis C virus (HCV) is exceptionally complex due to the highly diverse HCV genome. Genetic diversity, transmission dynamics, and epidemic history of the most common HCV genotypes were inferred by population sequencing of the HCV NS3, NS5A, and NS5B region followed by phylogenetic and phylodynamic analysis. The results of this research suggest high overall prevalence of baseline NS3 resistance associate substitutions (RAS) (33.0%), moderate prevalence of NS5A RAS (13.7%), and low prevalence of nucleoside inhibitor NS5B RAS (8.3%). Prevalence of RAS significantly differed according to HCV genotype, with the highest prevalence of baseline resistance to NS3 inhibitors and NS5A inhibitors observed in HCV subtype 1a (68.8%) and subtype 1b (21.3%), respectively. Phylogenetic tree reconstructions showed two distinct clades within the subtype 1a, clade I (62.4%) and clade II (37.6%). NS3 RAS were preferentially associated with clade I. Phylogenetic analysis demonstrated that 27 (9.0%) HCV sequences had a presumed epidemiological link with another sequence and classified into 13 transmission pairs or clusters which were predominantly comprised of subtype 3a viruses and commonly detected among intravenous drug users (IDU). Phylodynamic analyses highlighted an exponential increase in subtype 1a and 3a effective population size in the late 20th century, which is a period associated with an explosive increase in the number of IDU in Croatia.
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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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Shared HCV Transmission Networks Among HIV-1-Positive and HIV-1-Negative Men Having Sex With Men by Ultradeep Sequencing. J Acquir Immune Defic Syndr 2020; 82:105-110. [PMID: 31169768 DOI: 10.1097/qai.0000000000002099] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Several studies reported hepatitis C virus (HCV) transmission networks among men having sex with men (MSM) in Europe and the spread of HCV strains from HIV-HCV coinfected toward HCV monoinfected MSM. We aimed to investigate HCV transmission dynamics among HIV-positive and HIV-negative MSM by ultradeep sequencing (UDS). DESIGN AND METHODS NS5B fragment (388 bp) was sequenced from virus of 50 HIV-positive and 18 HIV-negative patients diagnosed with recent HCV infection. UDS data were analyzed by Geneious (version 10.3.2). Phylogenetic trees were constructed by FastTree (version 2.1) and submitted to ClusterPicker (version 1.2.3) for transmission chain detection at different thresholds of maximum genetic distance (MGD) (3% for Sanger, 3% and 4.5% for UDS). RESULTS Ten, 17, and 18 HCV transmission chains were identified by Sanger at 3%, UDS at 3% and at 4.5% of MGD, respectively. Of 68 subjects enrolled, 38 (55.9%), 38 (55.9%), and 43 (65.3%) individuals were involved in transmission networks found by Sanger at 3%, UDS at 3%, and at 4.5% of MGD, respectively. Mixed transmission chains including HIV-positive and HIV-negative subjects were detected for 8/10 chains by Sanger at 3%, for 9/17 by UDS at 3%, and for 10/18 by UDS at 4.5% of MGD. Overall, the number of HIV-negative individuals clustering with HIV-positive ones was 9/18 by Sanger, 9/18 by UDS at 3%, and 10/18 by UDS at 4.5% of MGD. CONCLUSIONS HIV-positive and HIV-negative MSM shared HCV transmission networks, which emphasizes the need for HCV surveillance and prevention measures in these communities regardless of the HIV status.
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Raghwani J, Wu CH, Ho CKY, De Jong M, Molenkamp R, Schinkel J, Pybus OG, Lythgoe KA. High-Resolution Evolutionary Analysis of Within-Host Hepatitis C Virus Infection. J Infect Dis 2020; 219:1722-1729. [PMID: 30602023 PMCID: PMC6500553 DOI: 10.1093/infdis/jiy747] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 12/28/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population. METHODS We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics. RESULTS We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10-7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection. CONCLUSIONS Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.
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Affiliation(s)
- Jayna Raghwani
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom
| | - Chieh-Hsi Wu
- Department of Statistics, University of Oxford, United Kingdom
| | - Cynthia K Y Ho
- Department of Medical Microbiology, Amsterdam University Medical Center, the Netherlands
| | - Menno De Jong
- Department of Medical Microbiology, Amsterdam University Medical Center, the Netherlands
| | - Richard Molenkamp
- Department of Medical Microbiology, Amsterdam University Medical Center, the Netherlands
| | - Janke Schinkel
- Department of Medical Microbiology, Amsterdam University Medical Center, the Netherlands
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, United Kingdom
| | - Katrina A Lythgoe
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom
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Ragonnet-Cronin M, Hostager R, Hedskog C, Osinusi A, Svarovskaia E, Wertheim JO. HIV co-infection is associated with increased transmission risk in patients with chronic hepatitis C virus. J Viral Hepat 2019; 26:1351-1354. [PMID: 31194901 PMCID: PMC6800583 DOI: 10.1111/jvh.13160] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/08/2019] [Accepted: 05/14/2019] [Indexed: 12/13/2022]
Abstract
Molecular epidemiological analysis of viral pathogens can identify factors associated with increased transmission risk. We investigated the frequency of genetic clustering in a large data set of NS34A, NS5A, and NS5B viral sequences from patients with chronic hepatitis C virus (HCV). Within a subset of patients with longitudinal samples, Receiver Operator Characteristic (ROC) analysis was applied which identified a threshold of 0.02 substitutions/site as most appropriate for clustering. From the 7457 patients with chronic HCV infection included in this analysis, we inferred 256 clusters comprising 541 patients (7.3%). We found that HCV/HIV co-infection, young age, and high HCV viral load were all associated with increased clustering frequency, an indicator of increased transmission risk. In light of previous work on HCV/HIV co-infection in acute HCV cohorts, our results suggest that patients with HCV/HIV co-infection may disproportionately be the source of new HCV infections and treatment efforts should be geared towards viral elimination in this vulnerable population.
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Affiliation(s)
- Manon Ragonnet-Cronin
- Department of Medicine, University of California San Diego, San Diego, California, USA,Current affiliation: Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Reilly Hostager
- Department of Medicine, University of California San Diego, San Diego, California, USA
| | | | - Ana Osinusi
- Gilead Sciences, Foster City, California, USA
| | | | - Joel O. Wertheim
- Department of Medicine, University of California San Diego, San Diego, California, USA,To whom correspondence should be addressed:
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Hackman J, Falade-Nwulia O, Patel EU, Mehta SH, Kirk GD, Astemborski J, Ray SC, Thomas DL, Laeyendecker O. Correlates of hepatitis C viral clustering among people who inject drugs in Baltimore. INFECTION GENETICS AND EVOLUTION 2019; 77:104078. [PMID: 31669367 DOI: 10.1016/j.meegid.2019.104078] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 10/07/2019] [Accepted: 10/19/2019] [Indexed: 01/15/2023]
Abstract
This study examines correlates of hepatitis C virus (HCV) genetic clustering among community-recruited people who inject drugs enrolled in the AIDS Linked to the IntraVenous Experience cohort in Baltimore between 1988 and 1989. HCV RNA was extracted and the core/envelope-1 region was sequenced. Clusters were identified from maximum likelihood trees with 1000 bootstrap replicates using a 70% aLRT and a 4% genetic-distance threshold in Cluster Picker. Overall, 46% of participants were in a cluster, including 122 genotype-1a and 36 genotype-1b clusters with an average of 2-3 genetically linked HCV infections. The largest cluster consists of 9 participants. In univariable analysis, black race (PR = 1.66 [95% CI: 1.12-2.45]), age <35 years (PR = 1.18 [95% CI: 1.02-1.37]), and injection drug use of cocaine alone (PR = 1.30 [95% CI: 1.02-1.65]) were significantly associated with being in a cluster. Conversely, a history of medication-associated treatment (MAT) was negatively associated with being in a cluster (PR = 0.82 [95% CI: 0.71-0.95]). In multivariable analysis, black race (APR = 1.62 [95% CI: 1.11-2.38]) remained independently associated being in a cluster while MAT (APR = 0.85 [95% CI: 0.74-0.99]) remained negatively associated with clustering. Our findings suggest strong locally-propagated transmission networks during the early epidemic that was driven by younger PWID. In light of the current opioid epidemic in the US, these findings suggest an urgent need for preventive interventions to mitigate the growth of large HCV transmission networks.
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Affiliation(s)
- Jada Hackman
- Division of Intramural Research, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States of America
| | - Oluwaseun Falade-Nwulia
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Eshan U Patel
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Shruti H Mehta
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Gregory D Kirk
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Jacquie Astemborski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Stuart C Ray
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - David L Thomas
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Oliver Laeyendecker
- Division of Intramural Research, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States of America; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
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Broadly Neutralizing Antibodies Targeting New Sites of Vulnerability in Hepatitis C Virus E1E2. J Virol 2019; 93:JVI.02070-18. [PMID: 31068427 DOI: 10.1128/jvi.02070-18] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 05/01/2019] [Indexed: 02/08/2023] Open
Abstract
Increasing evidence indicates that broadly neutralizing antibodies (bNAbs) play an important role in immune-mediated control of hepatitis C virus (HCV) infection, but the relative contribution of neutralizing antibodies targeting antigenic sites across the HCV envelope (E1 and E2) proteins is unclear. Here, we isolated thirteen E1E2-specific monoclonal antibodies (MAbs) from B cells of a single HCV-infected individual who cleared one genotype 1a infection and then became persistently infected with a second genotype 1a strain. These MAbs bound six distinct discontinuous antigenic sites on the E1 protein, the E2 protein, or the E1E2 heterodimer. Three antigenic sites, designated AS108, AS112 (an N-terminal E1 site), and AS146, were distinct from previously described antigenic regions (ARs) 1 to 5 and E1 sites. Antibodies targeting four sites (AR3, AR4-5, AS108, and AS146) were broadly neutralizing. These MAbs also displayed distinct patterns of relative neutralizing potency (i.e., neutralization profiles) across a panel of diverse HCV strains, which led to complementary neutralizing breadth when they were tested in combination. Overall, this study demonstrates that HCV bNAb epitopes are not restricted to previously described antigenic sites, expanding the number of sites that could be targeted for vaccine development.IMPORTANCE Worldwide, more than 70 million people are infected with hepatitis C virus (HCV), which is a leading cause of hepatocellular carcinoma and liver transplantation. Despite the development of potent direct acting antivirals (DAAs) for HCV treatment, a vaccine is urgently needed due to the high cost of treatment and the possibility of reinfection after cure. Induction of multiple broadly neutralizing antibodies (bNAbs) that target distinct epitopes on the HCV envelope proteins is one approach to vaccine development. However, antigenic sites targeted by bNAbs in individuals with spontaneous control of HCV have not been fully defined. In this study, we characterize 13 monoclonal antibodies (MAbs) from a single person who cleared an HCV infection without treatment, and we identify 3 new sites targeted by neutralizing antibodies. The sites targeted by these MAbs could inform HCV vaccine development.
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Kosakovsky Pond SL, Weaver S, Leigh Brown AJ, Wertheim JO. HIV-TRACE (TRAnsmission Cluster Engine): a Tool for Large Scale Molecular Epidemiology of HIV-1 and Other Rapidly Evolving Pathogens. Mol Biol Evol 2019; 35:1812-1819. [PMID: 29401317 DOI: 10.1093/molbev/msy016] [Citation(s) in RCA: 162] [Impact Index Per Article: 32.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoe-leather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, that is, on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from www.github.com/veg/hivtrace, along with the accompanying result visualization module from www.github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens.
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Affiliation(s)
| | - Steven Weaver
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
| | - Andrew J Leigh Brown
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Joel O Wertheim
- Department of Medicine, University of California, San Diego, CA
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Rose R, Rodriguez C, Dollar JJ, Lamers SL, Massaccesi G, Osburn W, Ray SC, Thomas DL, Cox AL, Laeyendecker O. Inconsistent temporal patterns of genetic variation of HCV among high-risk subjects may impact inference of transmission networks. INFECTION GENETICS AND EVOLUTION 2019; 71:1-6. [PMID: 30802530 DOI: 10.1016/j.meegid.2019.02.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 02/19/2019] [Accepted: 02/21/2019] [Indexed: 01/03/2023]
Abstract
Hepatitis-C Virus (HCV) sequences are often used to establish networks of people who inject drugs (PWID). However, the degree to which within-host evolutionary dynamics affect those inferences has not been carefully studied. Here, we analyzed 702 longitudinally-sampled HCV E1 sequences from 88 HCV+ people who inject drugs (PWID) in the Baltimore Before and After Acute Study of Hepatitis (BBAASH) cohort. Individuals were tested for HCV RNA over multiple visits to the clinic, and the HCV E1 gene was sequenced for HCV+ samples. Genetic clustering was performed on the full set of sequences using a 3% genetic distance threshold to define epidemiological linkage. Maximum-likelihood (ML) phylogenies were inferred to assess evolutionary relationships. We found 22 clusters containing sequences sampled over five or more years (long-term clusters, LTC), of which 17 had >1 subject. In six of the multi-subject LTC, one subject had a sequence sampled >3 years earlier or later than the next-closest subject in the cluster (time-gap LTC). ML trees showed that, in three of the time-gap LTC, two subjects had identical sequences despite 7-10 years separating the sampling times. In four of the time-gap LTC for whom additional data were available, the subject with the later detected shared variant had both different variants and visits with no detectable HCV RNA (RNA-) prior to the appearance of the shared variant. In the subject with the earlier detection of the shared variant, different variants and RNA- visits were also detected in multiple cases subsequent to appearance of the shared variant. Complex patterns of shared viral variation among PWID reflect on-going re-infection, multiple transmission partners, and/or inconsistent detection of viral variants. Our results suggest that transmission events are currently underestimated by analysis of sequences at a single point in time.
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Affiliation(s)
- Rebecca Rose
- BioInfoExperts LLC, Thibodaux, LA, United States.
| | | | | | | | - Guido Massaccesi
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - William Osburn
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Stuart C Ray
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - David L Thomas
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Andrea L Cox
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States; NIAID, NIH, Baltimore, MD, United States
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