1
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Neuner-Jehle N, Zeeb M, Thorball CW, Fellay J, Metzner KJ, Frischknecht P, Neumann K, Leeman C, Rauch A, Stöckle M, Huber M, Perreau M, Bernasconi E, Notter J, Hoffmann M, Leuzinger K, Günthard HF, Pasin C, Kouyos RD. Using viral diversity to identify HIV-1 variants under HLA-dependent selection in a systematic viral genome-wide screen. PLoS Pathog 2024; 20:e1012385. [PMID: 39116192 DOI: 10.1371/journal.ppat.1012385] [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: 12/19/2023] [Revised: 08/20/2024] [Accepted: 07/02/2024] [Indexed: 08/10/2024] Open
Abstract
The pathogenesis of HIV-1 infection is governed by a highly dynamic, time-dependent interaction between the host and the viral genome. In this study, we developed a novel systematic approach to assess the host-virus interaction, using average pairwise viral diversity as a proxy for time since infection, and applied this method to nearly whole viral genome sequences (n = 4,464), human leukocyte antigen (HLA) genotyping data (n = 1,044), and viral RNA load (VL) measurements during the untreated chronic phase (n = 829) of Swiss HIV Cohort Study participants. Our systematic genome-wide screen revealed for 98 HLA/viral-variant pairs a signature of immune-driven selection in the form of an HLA-dependent effect of infection time on the presence of HIV amino acid variants. Of these pairs, 12 were found to have an effect on VL. Furthermore, 28/58 pairs were validated by time-to-event analyses and 48/92 by computational HLA-epitope predictions. Our diversity-based approach allows a powerful and systematic investigation of the interaction between the virus and cellular immunity, revealing a notable subset of such interaction effects. From an evolutionary perspective, these observations underscore the complexity of HLA-mediated selection pressures on the virus that shape viral evolution and pathogenesis.
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Affiliation(s)
- Nadia Neuner-Jehle
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Marius Zeeb
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Christian W Thorball
- Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jacques Fellay
- Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Karin J Metzner
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Paul Frischknecht
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Kathrin Neumann
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Christine Leeman
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Marcel Stöckle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Matthieu Perreau
- Divisions of Immunology and Allergy, Lausanne University Hospital, Lausanne, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Ente Ospedaliero Cantonale, Lugano, University of Geneva and University of Southern Switzerland, Lugano, Switzerland
| | - Julia Notter
- Division of Infectious Diseases, Infection Prevention and Travel Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Matthias Hoffmann
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital Olten, Olten, Switzerland
| | | | - Huldrych F Günthard
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Chloé Pasin
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
- Collegium Helveticum, Zurich, Switzerland
| | - Roger D Kouyos
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
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2
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Zeeb M, Pasin C, Cavassini M, Bieler-Aeschlimann M, Frischknecht P, Kusejko K, Fellay J, Blanquart F, Metzner KJ, Neumann K, Jörimann L, Tschumi J, Bernasconi E, Huber M, Kovari H, Leuzinger K, Notter J, Perreau M, Rauch A, Ramette A, Stöckle M, Yerly S, Günthard HF, Kouyos RD. Self-reported neurocognitive complaints in the Swiss HIV Cohort Study: a viral genome-wide association study. Brain Commun 2024; 6:fcae188. [PMID: 38961872 PMCID: PMC11220509 DOI: 10.1093/braincomms/fcae188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 04/03/2024] [Accepted: 05/30/2024] [Indexed: 07/05/2024] Open
Abstract
People with HIV may report neurocognitive complaints, with or without associated neurocognitive impairment, varying between individuals and populations. While the HIV genome could play a major role, large systematic viral genome-wide screens to date are lacking. The Swiss HIV Cohort Study biannually enquires neurocognitive complaints. We quantified broad-sense heritability estimates using partial 'pol' sequences from the Swiss HIV Cohort Study resistance database and performed a viral near full-length genome-wide association study for the longitudinal area under the curve of neurocognitive complaints. We performed all analysis (i) restricted to HIV Subtype B and (ii) including all HIV subtypes. From 8547 people with HIV with neurocognitive complaints, we obtained 6966 partial 'pol' sequences and 2334 near full-length HIV sequences. Broad-sense heritability estimates for presence of memory loss complaints ranged between 1% and 17% (Subtype B restricted 1-22%) and increased with the stringency of the phylogenetic distance thresholds. The genome-wide association study revealed one amino acid (Env L641E), after adjusting for multiple testing, positively associated with memory loss complaints (P = 4.3 * 10-6). Other identified mutations, while insignificant after adjusting for multiple testing, were reported in other smaller studies (Tat T64N, Env *291S). We present the first HIV genome-wide association study analysis of neurocognitive complaints and report a first estimate for the heritability of neurocognitive complaints through HIV. Moreover, we could identify one mutation significantly associated with the presence of memory loss complaints. Our findings indicate that neurocognitive complaints are polygenetic and highlight advantages of a whole genome approach for pathogenicity determination.
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Affiliation(s)
- Marius Zeeb
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Chloé Pasin
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
| | - Mélanie Bieler-Aeschlimann
- Division of Infectious Diseases, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
| | - Paul Frischknecht
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Katharina Kusejko
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Jacques Fellay
- Division of Infectious Diseases, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
- Global Health Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - François Blanquart
- Centre interdisciplinaire de recherche en biologie, Collége de France, 75231 Paris, France
| | - Karin J Metzner
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Kathrin Neumann
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Lisa Jörimann
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Jasmin Tschumi
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Ente Ospedaliero Cantonale, 6500 Lugano, Switzerland
- Division of Infectious Diseases, University of Geneva and University of Southern Switzerland, 6900 Lugano, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Helen Kovari
- Center for Infectious Diseases, Klinik im Park, 8027 Zurich, Switzerland
| | - Karoline Leuzinger
- Division Infection Diagnostics, Department Biomedicine, University of Basel, 4001 Basel Switzerland
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, 4031 Basel, Switzerland
| | - Julia Notter
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, 9007 St. Gallen, Switzerland
| | - Matthieu Perreau
- Division of Immunology and Allergy, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases and Multidisciplinary Center for Infectious Diseases, University of Bern, 3012 Bern, Switzerland
| | - Marcel Stöckle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, 4031 Basel, Switzerland
| | - Sabine Yerly
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, University of Geneva, 1205 Geneva, Switzerland
| | - Huldrych F Günthard
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Roger D Kouyos
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
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3
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Zhang Z, Nishimura A, Trovão NS, Cherry JL, Holbrook AJ, Ji X, Lemey P, Suchard MA. Accelerating Bayesian inference of dependency between mixed-type biological traits. PLoS Comput Biol 2023; 19:e1011419. [PMID: 37639445 PMCID: PMC10491301 DOI: 10.1371/journal.pcbi.1011419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/08/2023] [Accepted: 08/09/2023] [Indexed: 08/31/2023] Open
Abstract
Inferring dependencies between mixed-type biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible when trait and specimen counts grow large. The state-of-the-art approach uses a phylogenetic multivariate probit model to accommodate binary and continuous traits via a latent variable framework, and utilizes an efficient bouncy particle sampler (BPS) to tackle the computational bottleneck-integrating many latent variables from a high-dimensional truncated normal distribution. This approach breaks down as the number of specimens grows and fails to reliably characterize conditional dependencies between traits. Here, we propose an inference pipeline for phylogenetic probit models that greatly outperforms BPS. The novelty lies in 1) a combination of the recent Zigzag Hamiltonian Monte Carlo (Zigzag-HMC) with linear-time gradient evaluations and 2) a joint sampling scheme for highly correlated latent variables and correlation matrix elements. In an application exploring HIV-1 evolution from 535 viruses, the inference requires joint sampling from an 11,235-dimensional truncated normal and a 24-dimensional covariance matrix. Our method yields a 5-fold speedup compared to BPS and makes it possible to learn partial correlations between candidate viral mutations and virulence. Computational speedup now enables us to tackle even larger problems: we study the evolution of influenza H1N1 glycosylations on around 900 viruses. For broader applicability, we extend the phylogenetic probit model to incorporate categorical traits, and demonstrate its use to study Aquilegia flower and pollinator co-evolution.
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Affiliation(s)
- Zhenyu Zhang
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
| | - Akihiko Nishimura
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Nídia S. Trovão
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Joshua L. Cherry
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Andrew J. Holbrook
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
| | - Xiang Ji
- Department of Mathematics, Tulane University, New Orleans, Louisiana, United States of America
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Marc A. Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
- Department of Biomathematics, University of California Los Angeles, Los Angeles, California, United States of America
- Department of Human Genetics, University of California Los Angeles, Los Angeles, California, United States of America
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4
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Real LM, Sáez ME, Corma-Gómez A, Gonzalez-Pérez A, Thorball C, Ruiz R, Jimenez-Leon MR, Gonzalez-Serna A, Gasca-Capote C, Bravo MJ, Royo JL, Perez-Gomez A, Camacho-Sojo MI, Gallego I, Vitalle J, Bachiller S, Gutierrez-Valencia A, Vidal F, Fellay J, Lichterfeld M, Ruiz-Mateos E. A metagenome-wide association study of HIV disease progression in HIV controllers. iScience 2023; 26:107214. [PMID: 37456859 PMCID: PMC10339206 DOI: 10.1016/j.isci.2023.107214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/19/2023] [Accepted: 06/22/2023] [Indexed: 07/18/2023] Open
Abstract
Some HIV controllers experience immunologic progression with CD4+ T cell decline. We aimed to identify genetic factors associated with CD4+ T cell lost in HIV controllers. A total of 561 HIV controllers were included, 442 and 119 from the International HIV controllers Study Cohort and the Swiss HIV Cohort Study, respectively. No SNP or gene was associated with the long-term non-progressor HIV spontaneous control phenotype in the individual GWAS or in the meta-analysis. However, SNPs previously associated with natural HIV control linked to HLA-B (rs2395029 [p = 0.005; OR = 1.70], rs59440261 [p = 0.003; OR = 1.78]), MICA (rs112243036 [p = 0.011; OR = 1.45]), and PSORS1C1 loci (rs3815087 [p = 0.017; OR = 1.39]) showed nominal association with this phenotype. Genetic factors associated with the long-term HIV controllers without risk of immunologic progression are those previously related to the overall HIV controller phenotype.
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Affiliation(s)
- Luis Miguel Real
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario Virgen de Valme, Instituto de Biomedicina de Sevilla, IBIS, Sevilla, Spain
- Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología, Facultad de Medicina, Universidad de Málaga, Málaga, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC)-Instituto de Salud Carlos III, Madrid, Spain
| | - María E. Sáez
- Centro Andaluz de Estudios Bioinformáticos (CAEBI, SL), Sevilla, Spain
| | - Anais Corma-Gómez
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario Virgen de Valme, Instituto de Biomedicina de Sevilla, IBIS, Sevilla, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC)-Instituto de Salud Carlos III, Madrid, Spain
| | | | - Christian Thorball
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Precision Medicine Unit, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Rocío Ruiz
- Departamento de Bioquímica y Biología Molecular, Facultad de Farmacia, Universidad de Sevilla/Instituto de Biomedicina de Sevilla-Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41012 Sevilla, Spain
| | - María Reyes Jimenez-Leon
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
| | - Alejandro Gonzalez-Serna
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario Virgen de Valme, Instituto de Biomedicina de Sevilla, IBIS, Sevilla, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC)-Instituto de Salud Carlos III, Madrid, Spain
| | - Carmen Gasca-Capote
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
| | - María José Bravo
- Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología, Facultad de Medicina, Universidad de Málaga, Málaga, Spain
| | - José Luis Royo
- Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología, Facultad de Medicina, Universidad de Málaga, Málaga, Spain
| | - Alberto Perez-Gomez
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
| | - María Inés Camacho-Sojo
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
| | - Isabel Gallego
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
| | - Joana Vitalle
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
| | - Sara Bachiller
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
- Department of Medical Biochemistry, Molecular Biology and Immunology, School of Medicine, University of Seville, Seville, Spain
| | - Alicia Gutierrez-Valencia
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
| | - Francisco Vidal
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC)-Instituto de Salud Carlos III, Madrid, Spain
- Hospital Universitari de Tarragona Joan XXIII (HJ23), Tarragona, Spain
- Institut Investigació Sanitària Pere Virgili (IISPV), Tarragona, Spain
- Universitat Rovira i Virgili (URV), Tarragona, Spain
| | - Jacques Fellay
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Precision Medicine Unit, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Mathias Lichterfeld
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Infectious Disease Division, Massachusetts General Hospital, Boston, MA, USA
- Infectious Disease Division, Brigham and Women’s Hospital, Boston, MA, USA
| | - Ezequiel Ruiz-Mateos
- Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine, Seville, Spain
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5
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Gabrielaite M, Bennedbæk M, Rasmussen MS, Kan V, Furrer H, Flisiak R, Losso M, Lundgren JD, Marvig RL. Deep-sequencing of viral genomes from a large and diverse cohort of treatment-naive HIV-infected persons shows associations between intrahost genetic diversity and viral load. PLoS Comput Biol 2023; 19:e1010756. [PMID: 36595537 PMCID: PMC9838853 DOI: 10.1371/journal.pcbi.1010756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/13/2023] [Accepted: 11/23/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Infection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, the association between intrahost diversity and disease progression markers has not been investigated in large and diverse cohorts for which the majority of the genome has been deep-sequenced. Viral load (VL) is a key progression marker and understanding of its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment. METHODS We analysed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between VL and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure. RESULTS We confirmed that the intrahost genetic diversity is highest in the env gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10-5) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL. Finally, equivalent analysis based on variation in HIV consensus sequences explained only 2% of VL variance. CONCLUSIONS Our results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes. TRIAL REGISTRATION Samples included in this study were derived from participants who consented in the clinical trial, START (NCT00867048) (23), run by the International Network for Strategic Initiatives in Global HIV Trials (INSIGHT). All the participant sites are listed here: http://www.insight-trials.org/start/my_phpscript/participating.php?by=site.
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Affiliation(s)
- Migle Gabrielaite
- Center for Genomic Medicine, Rigshospitalet, Copenhagen, Denmark
- * E-mail: (MG); (MB)
| | - Marc Bennedbæk
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- * E-mail: (MG); (MB)
| | - Malthe Sebro Rasmussen
- Center for Genomic Medicine, Rigshospitalet, Copenhagen, Denmark
- Section of Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Virginia Kan
- Veterans Affairs Medical Center and The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, United States of America
| | - Hansjakob Furrer
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Robert Flisiak
- Department of Infectious Diseases and Hepatology, Medical University of Bialystok, Bialystok, Poland
| | - Marcelo Losso
- Hospital General De Agudos J M Ramos Mejía, Buenos Aires, Argentina
| | - Jens D. Lundgren
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | | | - Rasmus L. Marvig
- Center for Genomic Medicine, Rigshospitalet, Copenhagen, Denmark
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6
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Fisher AA, Hassler GW, Ji X, Baele G, Suchard MA, Lemey P. Scalable Bayesian phylogenetics. Philos Trans R Soc Lond B Biol Sci 2022; 377:20210242. [PMID: 35989603 PMCID: PMC9393558 DOI: 10.1098/rstb.2021.0242] [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] [Indexed: 02/01/2023] Open
Abstract
Recent advances in Bayesian phylogenetics offer substantial computational savings to accommodate increased genomic sampling that challenges traditional inference methods. In this review, we begin with a brief summary of the Bayesian phylogenetic framework, and then conceptualize a variety of methods to improve posterior approximations via Markov chain Monte Carlo (MCMC) sampling. Specifically, we discuss methods to improve the speed of likelihood calculations, reduce MCMC burn-in, and generate better MCMC proposals. We apply several of these techniques to study the evolution of HIV virulence along a 1536-tip phylogeny and estimate the internal node heights of a 1000-tip SARS-CoV-2 phylogenetic tree in order to illustrate the speed-up of such analyses using current state-of-the-art approaches. We conclude our review with a discussion of promising alternatives to MCMC that approximate the phylogenetic posterior. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.
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Affiliation(s)
| | - Gabriel W. Hassler
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095, USA
| | - Xiang Ji
- Department of Mathematics, School of Science and Engineering, Tulane University, New Orleans, LA 70118, USA
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
| | - Marc A. Suchard
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095, USA,Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA,Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095, USA
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, 3000 Leuven, Belgium
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7
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Nadeau S, Thorball CW, Kouyos R, Günthard HF, Böni J, Yerly S, Perreau M, Klimkait T, Rauch A, Hirsch HH, Cavassini M, Vernazza P, Bernasconi E, Fellay J, Mitov V, Stadler T. A phylogeny-aware GWAS framework to correct for heritable pathogen effects on infectious disease traits. Mol Biol Evol 2022; 39:6654835. [PMID: 35921544 PMCID: PMC9366186 DOI: 10.1093/molbev/msac163] [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] [Indexed: 11/13/2022] Open
Abstract
Infectious diseases are particularly challenging for genome-wide association studies (GWAS) because genetic effects from two organisms (pathogen and host) can influence a trait. Traditional GWAS assume individual samples are independent observations. However, pathogen effects on a trait can be heritable from donor to recipient in transmission chains. Thus, residuals in GWAS association tests for host genetic effects may not be independent due to shared pathogen ancestry. We propose a new method to estimate and remove heritable pathogen effects on a trait based on the pathogen phylogeny prior to host GWAS, thus restoring independence of samples. In simulations, we show this additional step can increase GWAS power to detect truly associated host variants when pathogen effects are highly heritable, with strong phylogenetic correlations. We applied our framework to data from two different host-pathogen systems, HIV in humans and X. arboricola in A. thaliana. In both systems, the heritability and thus phylogenetic correlations turn out to be low enough such that qualitative results of GWAS do not change when accounting for the pathogen shared ancestry through a correction step. This means that previous GWAS results applied to these two systems should not be biased due to shared pathogen ancestry. In summary, our framework provides additional information on the evolutionary dynamics of traits in pathogen populations and may improve GWAS if pathogen effects are highly phylogenetically correlated amongst individuals in a cohort.
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Affiliation(s)
- Sarah Nadeau
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Christian W Thorball
- Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Roger Kouyos
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Huldrych F Günthard
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jürg Böni
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Sabine Yerly
- Division of Infectious Diseases, Laboratory of Virology, Geneva University Hospital, Geneva, Switzerland
| | - Matthieu Perreau
- Division of Immunology and Allergy, University Hospital Lausanne, Lausanne, Switzerland
| | - Thomas Klimkait
- Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Hans H Hirsch
- Department of Biomedicine, University of Basel, Basel, Switzerland.,Division of Clinical Virology, University Hospital Basel, Basel, Switzerland.,Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, University Hospital Lausanne, Lausanne, Switzerland
| | - Pietro Vernazza
- Division of Infectious Diseases, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Jacques Fellay
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Global Health Institute, School of Life Sciences, École Polytechnique FÉdÉrale de Lausanne, Lausanne, Switzerland
| | - Venelin Mitov
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
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8
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Umviligihozo G, Mann JK, Jin SW, Mwimanzi FM, Hsieh HSA, Sudderuddin H, Lee GQ, Byakwaga H, Muzoora C, Hunt PW, Martin JN, Haberer JE, Karita E, Allen S, Hunter E, Brumme ZL, Brockman MA. Attenuated HIV-1 Nef But Not Vpu Function in a Cohort of Rwandan Long-Term Survivors. FRONTIERS IN VIROLOGY 2022; 2:917902. [PMID: 35982753 PMCID: PMC9383652 DOI: 10.3389/fviro.2022.917902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
HIV-1 accessory proteins Nef and Vpu enhance viral pathogenesis through partially overlapping immune evasion activities. Attenuated Nef or Vpu functions have been reported in individuals who display slower disease progression, but few studies have assessed the relative impact of these proteins in non-B HIV-1 subtypes or examined paired proteins from the same individuals. Here, we examined the sequence and function of matched Nef and Vpu clones isolated from 29 long-term survivors (LTS) from Rwanda living with HIV-1 subtype A and compared our results to those of 104 Nef and 62 Vpu clones isolated from individuals living with chronic untreated HIV-1 subtype A from the same geographic area. Nef and vpu coding regions were amplified from plasma HIV RNA and cloned. The function of one intact, phylogenetically-validated Nef and Vpu clone per individual was then quantified by flow cytometry following transient expression in an immortalized CD4+ T-cell line. We measured the ability of each Nef clone to downregulate CD4 and HLA class I, and of each Vpu clone to downregulate CD4 and Tetherin, from the cell surface. Results were normalized to reference clones (Nef-SF2 and Vpu-NL4.3). We observed that Nef-mediated CD4 and HLA downregulation functions were lower in LTS compared to the control cohort (Mann-Whitney p=0.03 and p<0.0001, respectively). Moreover, we found a positive correlation between Nef-mediated CD4 downregulation function and plasma viral load in LTS and controls (Spearman ρ= 0.59, p=0.03 and ρ=0.30, p=0.005, respectively). In contrast, Vpu-mediated functions were similar between groups and did not correlate with clinical markers. Further analyses identified polymorphisms at Nef codon 184 and Vpu codons 60-62 that were associated with function, which were confirmed through mutagenesis. Overall, our results support attenuated function of Nef, but not Vpu, as a contributor to slower disease progression in this cohort of long-term survivors with HIV-1 subtype A.
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Affiliation(s)
| | - Jaclyn K. Mann
- HIV Pathogenesis Programme, University of KwaZulu-Natal, Durban, South Africa
| | - Steven W. Jin
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | | | - Hua-Shiuan A. Hsieh
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
| | - Hanwei Sudderuddin
- British Columbia Centre for Excellence in HIV/AIDS, Vancover, BC, Canada
| | - Guinevere Q. Lee
- Department of Medicine, Weill Cornell Medical College, New York, NY, United States
| | - Helen Byakwaga
- Department of Community Health, Mbarara University of Science and Technology, Mbarara, Uganda,Department of Medicine, University of California, San Francisco, CA, United States
| | - Conrad Muzoora
- Department of Medicine, Weill Cornell Medical College, New York, NY, United States
| | - Peter W. Hunt
- Department of Community Health, Mbarara University of Science and Technology, Mbarara, Uganda
| | - Jeff N. Martin
- Department of Community Health, Mbarara University of Science and Technology, Mbarara, Uganda
| | - Jessica E. Haberer
- Center for Global Health, Massachusetts General Hospital, Boston, MA, United States,Department of Medicine, Harvard Medical School, Boston, MA, United States
| | | | - Susan Allen
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States
| | - Eric Hunter
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States,Emory Vaccine Center at Yerkes National Primate Research Center, Atlanta, GA, United States
| | - Zabrina L. Brumme
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada,British Columbia Centre for Excellence in HIV/AIDS, Vancover, BC, Canada
| | - Mark A. Brockman
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada,Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada,British Columbia Centre for Excellence in HIV/AIDS, Vancover, BC, Canada,Correspondence: Mark A. Brockman,
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9
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Rindler AE, Kusejko K, Kuster H, Neumann K, Leemann C, Zeeb M, Chaudron SE, Braun DL, Kouyos RD, Metzner KJ, Günthard HF. The interplay between replication capacity of HIV-1 and surrogate markers of disease. J Infect Dis 2022; 226:1057-1068. [PMID: 35299248 DOI: 10.1093/infdis/jiac100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 03/16/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND HIV-1 replication capacity (RC) of transmitted/founder viruses may influence the further course of HIV-1 infection. METHODS Replication capacities (RCs) of 355 whole genome primary HIV-1 isolates derived from samples acquired during acute and recent primary HIV-1 infection (PHI) were determined using a novel high throughput infection assay in primary cells. The RCs were used to elucidate potential factors that could be associated with RC during PHI. RESULTS Increased RC was found to be associated with increased set point viral load (VL), and significant differences in RCs among 13 different HIV-1 subtypes were discerned. Notably, we observed an increase in RCs for primary HIV-1 isolates of HIV-1 subtype B over a 17-year period. Associations were not observed between RC and CD4 count at sample date of RC measurement, CD4 recovery after initiation of antiretroviral treatment (ART), CD4 decline in untreated individuals, and acute retroviral syndrome severity scores. DISCUSSION These findings highlight that RCs of primary HIV-1 isolates acquired during the acute and recent phase of infection are more associated with viral factors, i.e., set point VL, than with host factors. Furthermore, we observed a temporal increase in RC for HIV-1 subtype B viruses over a period of 17 years.
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Affiliation(s)
- Audrey E Rindler
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Life Science Zurich Graduate School, University of Zurich, Zurich, Switzerland
| | - Katharina Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Herbert Kuster
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Kathrin Neumann
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Christine Leemann
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Marius Zeeb
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Life Science Zurich Graduate School, University of Zurich, Zurich, Switzerland
| | - Sandra E Chaudron
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Life Science Zurich Graduate School, University of Zurich, Zurich, Switzerland
| | - Dominique L Braun
- Division 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
- Division 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
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Huldrych F Günthard
- Division 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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10
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Zhao L, Wymant C, Blanquart F, Golubchik T, Gall A, Bakker M, Bezemer D, Hall M, Ong SH, Albert J, Bannert N, Fellay J, Grabowski MK, Gunsenheimer-Bartmeyer B, Günthard HF, Kivelä P, Kouyos RD, Laeyendecker O, Meyer L, Porter K, van Sighem A, van der Valk M, Berkhout B, Kellam P, Cornelissen M, Reiss P, Fraser C, Ferretti L. Phylogenetic Estimation of the Viral Fitness Landscape of HIV-1 Set-Point Viral Load. Virus Evol 2022; 8:veac022. [PMID: 35402002 PMCID: PMC8986633 DOI: 10.1093/ve/veac022] [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: 11/11/2021] [Revised: 02/25/2022] [Accepted: 03/15/2022] [Indexed: 11/16/2022] Open
Abstract
Set-point viral load (SPVL), a common measure of human immunodeficiency virus (HIV)-1 virulence, is partially determined by viral genotype. Epidemiological evidence suggests that this viral property has been under stabilising selection, with a typical optimum for the virus between 104 and 105 copies of viral RNA per ml. Here we aimed to detect transmission fitness differences between viruses from individuals with different SPVLs directly from phylogenetic trees inferred from whole-genome sequences. We used the local branching index (LBI) as a proxy for transmission fitness. We found that LBI is more sensitive to differences in infectiousness than to differences in the duration of the infectious state. By analysing subtype-B samples from the Bridging the Evolution and Epidemiology of HIV in Europe project, we inferred a significant positive relationship between SPVL and LBI up to approximately 105 copies/ml, with some evidence for a peak around this value of SPVL. This is evidence of selection against low values of SPVL in HIV-1 subtype-B strains, likely related to lower infectiousness, and perhaps a peak in the transmission fitness in the expected range of SPVL. The less prominent signatures of selection against higher SPVL could be explained by an inherent limit of the method or the deployment of antiretroviral therapy.
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Affiliation(s)
- Lele Zhao
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - François Blanquart
- Centre for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France
| | - Tanya Golubchik
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Astrid Gall
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Margreet Bakker
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | | | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Swee Hoe Ong
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Jan Albert
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden
| | - Norbert Bannert
- Division for HIV and Other Retroviruses, Department of Infectious Diseases, Robert Koch Institute, Berlin, Germany
| | - Jacques Fellay
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - M Kate Grabowski
- Department of Pathology, John Hopkins University, Baltimore, MD, USA
| | | | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Pia Kivelä
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Laurence Meyer
- INSERM CESP U1018, Université Paris Saclay, APHP, Service de Santé Publique, Hôpital de Bicêtre, Le Kremlin-Bicêtre, France
| | - Kholoud Porter
- Institute for Global Health, University College London, London, UK
| | | | | | - Ben Berkhout
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Paul Kellam
- Kymab Ltd, Cambridge, UK
- Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London, UK
| | - Marion Cornelissen
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
- Molecular Diagnostic Unit, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Peter Reiss
- Stichting HIV Monitoring, Amsterdam, Netherlands
- Department of Global Health, Amsterdam University Medical Centers, University of Amsterdam and Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Luca Ferretti
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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11
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Wymant C, Bezemer D, Blanquart F, Ferretti L, Gall A, Hall M, Golubchik T, Bakker M, Ong SH, Zhao L, Bonsall D, de Cesare M, MacIntyre-Cockett G, Abeler-Dörner L, Albert J, Bannert N, Fellay J, Grabowski MK, Gunsenheimer-Bartmeyer B, Günthard HF, Kivelä P, Kouyos RD, Laeyendecker O, Meyer L, Porter K, Ristola M, van Sighem A, Berkhout B, Kellam P, Cornelissen M, Reiss P, Fraser C, Aubert V, Battegay M, Bernasconi E, Böni J, Braun DL, Bucher HC, Burton-Jeangros C, Calmy A, Cavassini M, Dollenmaier G, Egger M, Elzi L, Fehr J, Fellay J, Furrer H, Fux CA, Gorgievski M, Günthard H, Haerry D, Hasse B, Hirsch HH, Hoffmann M, Hösli I, Kahlert C, Kaiser L, Keiser O, Klimkait T, Kouyos R, Kovari H, Ledergerber B, Martinetti G, de Tejada BM, Marzolini C, Metzner K, Müller N, Nadal D, Nicca D, Pantaleo G, Rauch A, Regenass S, Rudin C, Schöni-Affolter F, Schmid P, Speck R, Stöckle M, Tarr P, Trkola A, Vernazza P, Weber R, Yerly S, van der Valk M, Geerlings SE, Goorhuis A, Hovius JW, Lempkes B, Nellen FJB, van der Poll T, Prins JM, Reiss P, van Vugt M, Wiersinga WJ, Wit FWMN, van Duinen M, van Eden J, Hazenberg A, van Hes AMH, Rajamanoharan S, Robinson T, Taylor B, Brewer C, Mayr C, Schmidt W, Speidel A, Strohbach F, Arastéh K, Cordes C, Pijnappel FJJ, Stündel M, Claus J, Baumgarten A, Carganico A, Ingiliz P, Dupke S, Freiwald M, Rausch M, Moll A, Schleehauf D, Smalhout SY, Hintsche B, Klausen G, Jessen H, Jessen A, Köppe S, Kreckel P, Schranz D, Fischer K, Schulbin H, Speer M, Weijsenfeld AM, Glaunsinger T, Wicke T, Bieniek B, Hillenbrand H, Schlote F, Lauenroth-Mai E, Schuler C, Schürmann D, Wesselmann H, Brockmeyer N, Jurriaans S, Gehring P, Schmalöer D, Hower M, Spornraft-Ragaller P, Häussinger D, Reuter S, Esser S, Markus R, Kreft B, Berzow D, Back NKT, Christl A, Meyer A, Plettenberg A, Stoehr A, Graefe K, Lorenzen T, Adam A, Schewe K, Weitner L, Fenske S, Zaaijer HL, Hansen S, Stellbrink HJ, Wiemer D, Hertling S, Schmidt R, Arbter P, Claus B, Galle P, Jäger H, Jä Gel-Guedes E, Berkhout B, Postel N, Fröschl M, Spinner C, Bogner J, Salzberger B, Schölmerich J, Audebert F, Marquardt T, Schaffert A, Schnaitmann E, Cornelissen MTE, Trein A, Frietsch B, Müller M, Ulmer A, Detering-Hübner B, Kern P, Schubert F, Dehn G, Schreiber M, Güler C, Schinkel CJ, Gunsenheimer-Bartmeyer B, Schmidt D, Meixenberger K, Bannert N, Wolthers KC, Peters EJG, van Agtmael MA, Autar RS, Bomers M, Sigaloff KCE, Heitmuller M, Laan LM, Ang CW, van Houdt R, Jonges M, Kuijpers TW, Pajkrt D, Scherpbier HJ, de Boer C, van der Plas A, van den Berge M, Stegeman A, Baas S, Hage de Looff L, Buiting A, Reuwer A, Veenemans J, Wintermans B, Pronk MJH, Ammerlaan HSM, van den Bersselaar DNJ, de Munnik ES, Deiman B, Jansz AR, Scharnhorst V, Tjhie J, Wegdam MCA, van Eeden A, Nellen J, Brokking W, Elsenburg LJM, Nobel H, van Kasteren MEE, Berrevoets MAH, Brouwer AE, Adams A, van Erve R, de Kruijf-van de Wiel BAFM, Keelan-Phaf S, van de Ven B, van der Ven B, Buiting AGM, Murck JL, de Vries-Sluijs TEMS, Bax HI, van Gorp ECM, de Jong-Peltenburg NC, de Mendonç A Melo M, van Nood E, Nouwen JL, Rijnders BJA, Rokx C, Schurink CAM, Slobbe L, Verbon A, Bassant N, van Beek JEA, Vriesde M, van Zonneveld LM, de Groot J, Boucher CAB, Koopmans MPG, van Kampen JJA, Fraaij PLA, van Rossum AMC, Vermont CL, van der Knaap LC, Visser E, Branger J, Douma RA, Cents-Bosma AS, Duijf-van de Ven CJHM, Schippers EF, van Nieuwkoop C, van Ijperen JM, Geilings J, van der Hut G, van Burgel ND, Leyten EMS, Gelinck LBS, Mollema F, Davids-Veldhuis S, Tearno C, Wildenbeest GS, Heikens E, Groeneveld PHP, Bouwhuis JW, Lammers AJJ, Kraan S, van Hulzen AGW, Kruiper MSM, van der Bliek GL, Bor PCJ, Debast SB, Wagenvoort GHJ, Kroon FP, de Boer MGJ, Jolink H, Lambregts MMC, Roukens AHE, Scheper H, Dorama W, van Holten N, Claas ECJ, Wessels E, den Hollander JG, El Moussaoui R, Pogany K, Brouwer CJ, Smit JV, Struik-Kalkman D, van Niekerk T, Pontesilli O, Lowe SH, Oude Lashof AML, Posthouwer D, van Wolfswinkel ME, Ackens RP, Burgers K, Schippers J, Weijenberg-Maes B, van Loo IHM, Havenith TRA, van Vonderen MGA, Kampschreur LM, Faber S, Steeman-Bouma R, Al Moujahid A, Kootstra GJ, Delsing CE, van der Burg-van de Plas M, Scheiberlich L, Kortmann W, van Twillert G, Renckens R, Ruiter-Pronk D, van Truijen-Oud FA, Cohen Stuart JWT, Jansen ER, Hoogewerf M, Rozemeijer W, van der Reijden WA, Sinnige JC, Brinkman K, van den Berk GEL, Blok WL, Lettinga KD, de Regt M, Schouten WEM, Stalenhoef JE, Veenstra J, Vrouenraets SME, Blaauw H, Geerders GF, Kleene MJ, Kok M, Knapen M, van der Meché IB, Mulder-Seeleman E, Toonen AJM, Wijnands S, Wttewaal E, Kwa D, van Crevel R, van Aerde K, Dofferhoff ASM, Henriet SSV, Ter Hofstede HJM, Hoogerwerf J, Keuter M, Richel O, Albers M, Grintjes-Huisman KJT, de Haan M, Marneef M, Strik-Albers R, Rahamat-Langendoen J, Stelma FF, Burger D, Gisolf EH, Hassing RJ, Claassen M, Ter Beest G, van Bentum PHM, Langebeek N, Tiemessen R, Swanink CMA, van Lelyveld SFL, Soetekouw R, van der Prijt LMM, van der Swaluw J, Bermon N, van der Reijden WA, Jansen R, Herpers BL, Veenendaal D, Verhagen DWM, Lauw FN, van Broekhuizen MC, van Wijk M, Bierman WFW, Bakker M, Kleinnijenhuis J, Kloeze E, Middel A, Postma DF, Schölvinck EH, Stienstra Y, Verhage AR, Wouthuyzen-Bakker M, Boonstra A, de Groot-de Jonge H, van der Meulen PA, de Weerd DA, Niesters HGM, van Leer-Buter CC, Knoester M, Hoepelman AIM, Arends JE, Barth RE, Bruns AHW, Ellerbroek PM, Mudrikova T, Oosterheert JJ, Schadd EM, van Welzen BJ, Aarsman K, Griffioen-van Santen BMG, de Kroon I, van Berkel M, van Rooijen CSAM, Schuurman R, Verduyn-Lunel F, Wensing AMJ, Bont LJ, Geelen SPM, Loeffen YGT, Wolfs TFW, Nauta N, Rooijakkers EOW, Holtsema H, Voigt R, van de Wetering D, Alberto A, van der Meer I, Rosingh A, Halaby T, Zaheri S, Boyd AC, Bezemer DO, van Sighem AI, Smit C, Hillebregt M, de Jong A, Woudstra T, Bergsma D, Meijering R, van de Sande L, Rutkens T, van der Vliet S, de Groot L, van den Akker M, Bakker Y, El Berkaoui A, Bezemer M, Brétin N, Djoechro E, Groters M, Kruijne E, Lelivelt KJ, Lodewijk C, Lucas E, Munjishvili L, Paling F, Peeck B, Ree C, Regtop R, Ruijs Y, Schoorl M, Schnörr P, Scheigrond A, Tuijn E, Veenenberg L, Visser KM, Witte EC, Ruijs Y, Van Frankenhuijsen M, Allegre T, Makhloufi D, Livrozet JM, Chiarello P, Godinot M, Brunel-Dalmas F, Gibert S, Trepo C, Peyramond D, Miailhes P, Koffi J, Thoirain V, Brochier C, Baudry T, Pailhes S, Lafeuillade A, Philip G, Hittinger G, Assi A, Lambry V, Rosenthal E, Naqvi A, Dunais B, Cua E, Pradier C, Durant J, Joulie A, Quinsat D, Tempesta S, Ravaux I, Martin IP, Faucher O, Cloarec N, Champagne H, Pichancourt G, Morlat P, Pistone T, Bonnet F, Mercie P, Faure I, Hessamfar M, Malvy D, Lacoste D, Pertusa MC, Vandenhende MA, Bernard N, Paccalin F, Martell C, Roger-Schmelz J, Receveur MC, Duffau P, Dondia D, Ribeiro E, Caltado S, Neau D, Dupont M, Dutronc H, Dauchy F, Cazanave C, Vareil MO, Wirth G, Le Puil S, Pellegrin JL, Raymond I, Viallard JF, Chaigne de Lalande S, Garipuy D, Delobel P, Obadia M, Cuzin L, Alvarez M, Biezunski N, Porte L, Massip P, Debard A, Balsarin F, Lagarrigue M, Prevoteau du Clary F, Aquilina C, Reynes J, Baillat V, Merle C, Lemoing V, Atoui N, Makinson A, Jacquet JM, Psomas C, Tramoni C, Aumaitre H, Saada M, Medus M, Malet M, Eden A, Neuville S, Ferreyra M, Sotto A, Barbuat C, Rouanet I, Leureillard D, Mauboussin JM, Lechiche C, Donsesco R, Cabie A, Abel S, Pierre-Francois S, Batala AS, Cerland C, Rangom C, Theresine N, Hoen B, Lamaury I, Fabre I, Schepers K, Curlier E, Ouissa R, Gaud C, Ricaud C, Rodet R, Wartel G, Sautron C, Beck-Wirth G, Michel C, Beck C, Halna JM, Kowalczyk J, Benomar M, Drobacheff-Thiebaut C, Chirouze C, Faucher JF, Parcelier F, Foltzer A, Haffner-Mauvais C, Hustache Mathieu M, Proust A, Piroth L, Chavanet P, Duong M, Buisson M, Waldner A, Mahy S, Gohier S, Croisier D, May T, Delestan M, Andre M, Zadeh MM, Martinot M, Rosolen B, Pachart A, Martha B, Jeunet N, Rey D, Cheneau C, Partisani M, Priester M, Bernard-Henry C, Batard ML, Fischer P, Berger JL, Kmiec I, Robineau O, Huleux T, Ajana F, Alcaraz I, Allienne C, Baclet V, Meybeck A, Valette M, Viget N, Aissi E, Biekre R, Cornavin P, Merrien D, Seghezzi JC, Machado M, Diab G, Raffi F, Bonnet B, Allavena C, Grossi O, Reliquet V, Billaud E, Brunet C, Bouchez S, Morineau-Le Houssine P, Sauser F, Boutoille D, Besnier M, Hue H, Hall N, Brosseau D, Souala F, Michelet C, Tattevin P, Arvieux C, Revest M, Leroy H, Chapplain JM, Dupont M, Fily F, Patra-Delo S, Lefeuvre C, Bernard L, Bastides F, Nau P, Verdon R, de la Blanchardiere A, Martin A, Feret P, Geffray L, Daniel C, Rohan J, Fialaire P, Chennebault JM, Rabier V, Abgueguen P, Rehaiem S, Luycx O, Niault M, Moreau P, Poinsignon Y, Goussef M, Mouton-Rioux V, Houlbert D, Alvarez-Huve S, Barbe F, Haret S, Perre P, Leantez-Nainville S, Esnault JL, Guimard T, Suaud I, Girard JJ, Simonet V, Debab Y, Schmit JL, Jacomet C, Weinberck P, Genet C, Pinet P, Ducroix S, Durox H, Denes É, Abraham B, Gourdon F, Antoniotti O, Molina JM, Ferret S, Lascoux-Combe C, Lafaurie M, Colin de Verdiere N, Ponscarme D, De Castro N, Aslan A, Rozenbaum W, Pintado C, Clavel F, Taulera O, Gatey C, Munier AL, Gazaigne S, Penot P, Conort G, Lerolle N, Leplatois A, Balausine S, Delgado J, Timsit J, Tabet M, Gerard L, Girard PM, Picard O, Tredup J, Bollens D, Valin N, Campa P, Bottero J, Lefebvre B, Tourneur M, Fonquernie L, Wemmert C, Lagneau JL, Yazdanpanah Y, Phung B, Pinto A, Vallois D, Cabras O, Louni F, Pialoux G, Lyavanc T, Berrebi V, Chas J, Lenagat S, Rami A, Diemer M, Parrinello M, Depond A, Salmon D, Guillevin L, Tahi T, Belarbi L, Loulergue P, Zak Dit Zbar O, Launay O, Silbermann B, Leport C, Alagna L, Pietri MP, Simon A, Bonmarchand M, Amirat N, Pichon F, Kirstetter M, Katlama C, Valantin MA, Tubiana R, Caby F, Schneider L, Ktorza N, Calin R, Merlet A, Ben Abdallah S, Weiss L, Buisson M, Batisse D, Karmochine M, Pavie J, Minozzi C, Jayle D, Castel P, Derouineau J, Kousignan P, Eliazevitch M, Pierre I, Collias L, Viard JP, Gilquin J, Sobel A, Slama L, Ghosn J, Hadacek B, Thu-Huyn N, Nait-Ighil L, Cros A, Maignan A, Duvivier C, Consigny PH, Lanternier F, Shoai-Tehrani M, Touam F, Jerbi S, Bodard L, Jung C, Goujard C, Quertainmont Y, Duracinsky M, Segeral O, Blanc A, Peretti D, Cheret A, Chantalat C, Dulucq MJ, Levy Y, Lelievre JD, Lascaux AS, Dumont C, Boue F, Chambrin V, Abgrall S, Kansau I, Raho-Moussa M, De Truchis P, Dinh A, Davido B, Marigot D, Berthe H, Devidas A, Chevojon P, Chabrol A, Agher N, Lemercier Y, Chaix F, Turpault I, Bouchaud O, Honore P, Rouveix E, Reimann E, Belan AG, Godin Collet C, Souak S, Mortier E, Bloch M, Simonpoli AM, Manceron V, Cahitte I, Hiraux E, Lafon E, Cordonnier F, Zeng AF, Zucman D, Majerholc C, Bornarel D, Uludag A, Gellen-Dautremer J, Lefort A, Bazin C, Daneluzzi V, Gerbe J, Jeantils V, Coupard M, Patey O, Bantsimba J, Delllion S, Paz PC, Cazenave B, Richier L, Garrait V, Delacroix I, Elharrar B, Vittecoq D, Bolliot C, Lepretre A, Genet P, Masse V, Perrone V, Boussard JL, Chardon P, Froguel E, Simon P, Tassi S, Avettand Fenoel V, Barin F, Bourgeois C, Cardon F, Chaix ML, Delfraissy JF, Essat A, Fischer H, Lecuroux C, Meyer L, Petrov-Sanchez V, Rouzioux C, Saez-Cirion A, Seng R, Kuldanek K, Mullaney S, Young C, Zucchetti A, Bevan MA, McKernan S, Wandolo E, Richardson C, Youssef E, Green P, Faulkner S, Faville R, Herman S, Care C, Blackman H, Bellenger K, Fairbrother K, Phillips A, Babiker A, Delpech V, Fidler S, Clarke M, Fox J, Gilson R, Goldberg D, Hawkins D, Johnson A, Johnson M, McLean K, Nastouli E, Post F, Kennedy N, Pritchard J, Andrady U, Rajda N, Donnelly C, McKernan S, Drake S, Gilleran G, White D, Ross J, Harding J, Faville R, Sweeney J, Flegg P, Toomer S, Wilding H, Woodward R, Dean G, Richardson C, Perry N, Gompels M, Jennings L, Bansaal D, Browing M, Connolly L, Stanley B, Estreich S, Magdy A, O'Mahony C, Fraser P, Jebakumar SPR, David L, Mette R, Summerfield H, Evans M, White C, Robertson R, Lean C, Morris S, Winter A, Faulkner S, Goorney B, Howard L, Fairley I, Stemp C, Short L, Gomez M, Young F, Roberts M, Green S, Sivakumar K, Minton J, Siminoni A, Calderwood J, Greenhough D, DeSouza C, Muthern L, Orkin C, Murphy S, Truvedi M, McLean K, Hawkins D, Higgs C, Moyes A, Antonucci S, McCormack S, Lynn W, Bevan M, Fox J, Teague A, Anderson J, Mguni S, Post F, Campbell L, Mazhude C, Russell H, Gilson R, Carrick G, Ainsworth J, Waters A, Byrne P, Johnson M, Fidler S, Kuldanek K, Mullaney S, Lawlor V, Melville R, Sukthankar A, Thorpe S, Murphy C, Wilkins E, Ahmad S, Green P, Tayal S, Ong E, Meaden J, Riddell L, Loay D, Peacock K, Blackman H, Harindra V, Saeed AM, Allen S, Natarajan U, Williams O, Lacey H, Care C, Bowman C, Herman S, Devendra SV, Wither J, Bridgwood A, Singh G, Bushby S, Kellock D, Young S, Rooney G, Snart B, Currie J, Fitzgerald M, Arumainayyagam J, Chandramani S. A highly virulent variant of HIV-1 circulating in the Netherlands. Science 2022; 375:540-545. [PMID: 35113714 DOI: 10.1126/science.abk1688] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log10 increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence.
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Affiliation(s)
- Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - François Blanquart
- Centre for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France.,IAME, UMR 1137, INSERM, Université de Paris, Paris, France
| | - Luca Ferretti
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Astrid Gall
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Tanya Golubchik
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Margreet Bakker
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Swee Hoe Ong
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Lele Zhao
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - David Bonsall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Mariateresa de Cesare
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - George MacIntyre-Cockett
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lucie Abeler-Dörner
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jan Albert
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden
| | - Norbert Bannert
- Division for HIV and Other Retroviruses, Department of Infectious Diseases, Robert Koch Institute, Berlin, Germany
| | - Jacques Fellay
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - M Kate Grabowski
- Department of Pathology, John Hopkins University, Baltimore, MD, USA
| | | | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Pia Kivelä
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Laurence Meyer
- INSERM CESP U1018, Université Paris Saclay, APHP, Service de Santé Publique, Hôpital de Bicêtre, Le Kremlin-Bicêtre, France
| | - Kholoud Porter
- Institute for Global Health, University College London, London, UK
| | - Matti Ristola
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | | | - Ben Berkhout
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Paul Kellam
- Kymab Ltd., Cambridge, UK.,Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London, UK
| | - Marion Cornelissen
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.,Molecular Diagnostic Unit, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Peter Reiss
- Stichting HIV Monitoring, Amsterdam, Netherlands.,Department of Global Health, Amsterdam University Medical Centers, University of Amsterdam and Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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Dijkstra M, Prins H, Prins JM, Reiss P, Boucher C, Verbon A, Rokx C, de Bree G. Cohort profile: the Netherlands Cohort Study on Acute HIV infection (NOVA), a prospective cohort study of people with acute or early HIV infection who immediately initiate HIV treatment. BMJ Open 2021; 11:e048582. [PMID: 34845066 PMCID: PMC8634014 DOI: 10.1136/bmjopen-2020-048582] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 10/14/2021] [Indexed: 11/03/2022] Open
Abstract
PURPOSE Initiation of combination antiretroviral therapy (cART) during acute or early HIV-infection (AEHI) limits the size of the viral reservoir and preserves immune function. This renders individuals who started cART during AEHI promising participants in HIV-cure trials. Therefore, we established a multicentre prospective cohort study in the Netherlands that enrols people with AEHI. In anticipation of future cure trials, we will longitudinally investigate the properties of the viral reservoir size and HIV-specific immune responses among cohort participants. PARTICIPANTS Participants immediately initiate intensified cART: dolutegravir, emtricitabine/tenofovir and darunavir/ritonavir (DRV/r). After 4 weeks, once baseline resistance data are available, DRV/r is discontinued. Three study groups are assembled based on the preparedness of individuals to participate in the extensiveness of sampling. Participants accepting immediate treatment and follow-up but declining additional sampling are included in study group 1 ('standard') and routine diagnostic procedures are performed. Participants willing to undergo blood, leukapheresis and semen sampling are included in study group 2 ('less invasive'). In study group 3 ('extended'), additional tissue (gut-associated lymphoid tissue, peripheral lymph node) and cerebrospinal fluid sampling are performed. FINDINGS TO DATE Between 2015 and 2020, 140 individuals with AEHI have been enrolled at nine study sites. At enrolment, median age was 36 (IQR 28-47) years, and 134 (95.7%) participants were men. Distribution of Fiebig stages was as follows: Fiebig I, 3 (2.1%); II, 20 (14.3%); III, 7 (5.0%); IV, 49 (35.0%); V, 39 (27.9%); VI, 22 (15.7%). Median plasma HIV RNA was 5.9 (IQR 4.7-6.7) log10 copies/mL and CD4 count 510 (IQR 370-700) cells/mm3. Median time from cART initiation to viral suppression was 8.0 (IQR 4.0-16.0) weeks. FUTURE PLANS The Netherlands Cohort Study on Acute HIV infection remains open for participant enrolment and for additional sites to join the network. This cohort provides a unique nationwide platform for conducting future in-depth virological, immunological, host genetic and interventional studies investigating HIV-cure strategies.
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Affiliation(s)
- Maartje Dijkstra
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, Netherlands
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam Institute for Infection and Immunity (AII), Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Henrieke Prins
- Department of Internal Medicine, Division of Infectious Diseases, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Jan M Prins
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam Institute for Infection and Immunity (AII), Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Peter Reiss
- Department of Internal Medicine, Division of Infectious Diseases, Amsterdam Institute for Infection and Immunity (AII), Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
- HIV Monitoring Foundation, Amsterdam, Noord-Holland, Netherlands
- Department of Global Health, Amsterdam Institute for Global Health and Development, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Charles Boucher
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Annelies Verbon
- Department of Internal Medicine, Division of Infectious Diseases, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Casper Rokx
- Department of Internal Medicine, Division of Infectious Diseases, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Godelieve de Bree
- Department of Internal Medicine, Amsterdam University Medical Centre, Amsterdam, Netherlands
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13
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Gabrielaite M, Bennedbæk M, Zucco AG, Ekenberg C, Murray DD, Kan VL, Touloumi G, Vandekerckhove L, Turner D, Neaton J, Lane HC, Safo S, Arenas-Pinto A, Polizzotto MN, Günthard HF, Lundgren JD, Marvig RL. Human immunotypes impose selection on viral genotypes through viral epitope specificity. J Infect Dis 2021; 224:2053-2063. [PMID: 33974707 DOI: 10.1093/infdis/jiab253] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 05/06/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Understanding the genetic interplay between human hosts and infectious pathogens is crucial for how we interpret virulence factors. Here, we tested for associations between HIV and host genetics, and interactive genetic effects on viral load (VL) in HIV+ ART-naive clinical trial participants. METHODS HIV genomes were sequenced and the encoded amino acid (AA) variants were associated with VL, human single nucleotide polymorphisms (SNPs) and imputed HLA alleles, using generalized linear models with Bonferroni correction. RESULTS Human (388,501 SNPs) and HIV (3,010 variants) genetic data was available for 2,122 persons. Four HIV variants were associated with VL (p-values<1.66×10 -5). Twelve HIV variants were associated with a range of 1-512 human SNPs (p-value<4.28×10 -11). We found 46 associations between HLA alleles and HIV variants (p-values<1.29×10 -7). We found HIV variants and immunotypes when analyzed separately, were associated with lower VL, whereas the opposite was true when analyzed in concert. Epitope binding prediction showed HLA alleles to be weaker binders of associated HIV AA variants relative to alternative variants on the same position. CONCLUSIONS Our results show the importance of immunotype specificity on viral antigenic determinants, and the identified genetic interplay puts emphasis that viral and human genetics should be studied in the context of each other.
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Affiliation(s)
- Migle Gabrielaite
- Centre for Genomic Medicine, Copenhagen University Hospital, Copenhagen, Denmark
| | - Marc Bennedbæk
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Adrian G Zucco
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Christina Ekenberg
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Daniel D Murray
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Virginia L Kan
- Veterans Affairs Medical Center, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Giota Touloumi
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Linos Vandekerckhove
- HIV Cure Research Center, Department of Internal Medicine and Pediatrics, Faculty of Medicine and Health Sciences, Ghent University; Ghent University Hospital, Ghent, Belgium
| | - Dan Turner
- Crusaid Kobler AIDS Center, Tel-Aviv Sourasky Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - James Neaton
- School of Public Health, University of Minnesota, Minneapolis, USA
| | - H Clifford Lane
- Division of Clinical Research, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, Maryland, USA
| | - Sandra Safo
- Division of Biostatistics, University of Minnesota, Minneapolis, USA
| | | | - Mark N Polizzotto
- Kirby Institute for Infection and Immunity, University of New South Wales, Sydney, Australia
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Zürich, Switzerland.,Institute of Medical Virology, University of Zürich, Zürich, Switzerland
| | - Jens D Lundgren
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Rasmus L Marvig
- Centre for Genomic Medicine, Copenhagen University Hospital, Copenhagen, Denmark
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14
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Heritability of the HIV-1 reservoir size and decay under long-term suppressive ART. Nat Commun 2020; 11:5542. [PMID: 33139735 PMCID: PMC7608612 DOI: 10.1038/s41467-020-19198-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 09/23/2020] [Indexed: 12/02/2022] Open
Abstract
The HIV-1 reservoir is the major hurdle to curing HIV-1. However, the impact of the viral genome on the HIV-1 reservoir, i.e. its heritability, remains unknown. We investigate the heritability of the HIV-1 reservoir size and its long-term decay by analyzing the distribution of those traits on viral phylogenies from both partial-pol and viral near full-length genome sequences. We use a unique nationwide cohort of 610 well-characterized HIV-1 subtype-B infected individuals on suppressive ART for a median of 5.4 years. We find that a moderate but significant fraction of the HIV-1 reservoir size 1.5 years after the initiation of ART is explained by genetic factors. At the same time, we find more tentative evidence for the heritability of the long-term HIV-1 reservoir decay. Our findings indicate that viral genetic factors contribute to the HIV-1 reservoir size and hence the infecting HIV-1 strain may affect individual patients’ hurdle towards a cure. The HIV reservoir is a major hurdle for a cure of HIV, but the factors determining its size and dynamics remain unclear. Here the authors show in a large cohort of 610 HIV-1 infected individuals, who are on suppressive ART for a median of 5.4 years, that viral genetic factors contribute substantially to the HIV-1 reservoir size.
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15
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Adikari TN, Riaz N, Sigera C, Leung P, Valencia BM, Barton K, Smith MA, Bull RA, Li H, Luciani F, Weeratunga P, Thein TL, Lim VWX, Leo YS, Rajapakse S, Fink K, Lloyd AR, Fernando D, Rodrigo C. Single molecule, near full-length genome sequencing of dengue virus. Sci Rep 2020; 10:18196. [PMID: 33097792 PMCID: PMC7584602 DOI: 10.1038/s41598-020-75374-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 10/12/2020] [Indexed: 01/23/2023] Open
Abstract
Current methods for dengue virus (DENV) genome amplification, amplify parts of the genome in at least 5 overlapping segments and then combine the output to characterize a full genome. This process is laborious, costly and requires at least 10 primers per serotype, thus increasing the likelihood of PCR bias. We introduce an assay to amplify near full-length dengue virus genomes as intact molecules, sequence these amplicons with third generation “nanopore” technology without fragmenting and use the sequence data to differentiate within-host viral variants with a bioinformatics tool (Nano-Q). The new assay successfully generated near full-length amplicons from DENV serotypes 1, 2 and 3 samples which were sequenced with nanopore technology. Consensus DENV sequences generated by nanopore sequencing had over 99.5% pairwise sequence similarity to Illumina generated counterparts provided the coverage was > 100 with both platforms. Maximum likelihood phylogenetic trees generated from nanopore consensus sequences were able to reproduce the exact trees made from Illumina sequencing with a conservative 99% bootstrapping threshold (after 1000 replicates and 10% burn-in). Pairwise genetic distances of within host variants identified from the Nano-Q tool were less than that of between host variants, thus enabling the phylogenetic segregation of variants from the same host.
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Affiliation(s)
- Thiruni N Adikari
- School of Medical Sciences, University of New South Wales, Sydney, Australia.,Institute for Combinatorial Advanced Research and Education, Sir John Kotelawala Defence University, Ratmalana, Sri Lanka
| | - Nasir Riaz
- Kirby Institute, University of New South Wales, Sydney, Australia.,Department of Microbiology, Hazara University, Mansehra, KPK, Pakistan
| | - Chathurani Sigera
- Department of Parasitology, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | - Preston Leung
- Kirby Institute, University of New South Wales, Sydney, Australia
| | | | - Kirston Barton
- Garvan Institute of Medical Research, Sydney, Australia and St-Vincent's Clinical School, Faculty of Medicine, UNSW, Sydney, Australia
| | - Martin A Smith
- Garvan Institute of Medical Research, Sydney, Australia and St-Vincent's Clinical School, Faculty of Medicine, UNSW, Sydney, Australia.,CHU Sainte-Justine Research Centre, Montreal, Canada.,Department of Biochemistry and Molecular Medicine, Université de Montréal, Montreal, Canada
| | - Rowena A Bull
- School of Medical Sciences, University of New South Wales, Sydney, Australia.,Kirby Institute, University of New South Wales, Sydney, Australia
| | - Hui Li
- Kirby Institute, University of New South Wales, Sydney, Australia
| | - Fabio Luciani
- School of Medical Sciences, University of New South Wales, Sydney, Australia.,Kirby Institute, University of New South Wales, Sydney, Australia
| | - Praveen Weeratunga
- Department of Clinical Medicine, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | - Tun-Linn Thein
- National Centre for Infectious Diseases, Singapore, Singapore
| | - Vanessa W X Lim
- National Centre for Infectious Diseases, Singapore, Singapore
| | - Yee-Sin Leo
- National Centre for Infectious Diseases, Singapore, Singapore.,Department of Infectious Diseases, Tan Tock Seng Hospital, Singapore, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Lee Kong Chian School of Medicine, Singapore, Singapore
| | - Senaka Rajapakse
- Department of Clinical Medicine, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | - Katja Fink
- Agency for Science, Technology and Research, Singapore, Singapore
| | - Andrew R Lloyd
- Kirby Institute, University of New South Wales, Sydney, Australia
| | - Deepika Fernando
- Department of Parasitology, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | - Chaturaka Rodrigo
- School of Medical Sciences, University of New South Wales, Sydney, Australia. .,Kirby Institute, University of New South Wales, Sydney, Australia.
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16
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Downs LO, Vawda S, Bester PA, Lythgoe KA, Wang T, McNaughton AL, Smith DA, Maponga T, Freeman O, Várnai KA, Davies J, Woods K, Fraser C, Barnes E, Goedhals D, Matthews PC. Bimodal distribution and set point HBV DNA viral loads in chronic infection: retrospective analysis of cohorts from the UK and South Africa. Wellcome Open Res 2020; 5:113. [PMID: 33274299 PMCID: PMC7682492 DOI: 10.12688/wellcomeopenres.15941.2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/22/2020] [Indexed: 12/19/2022] Open
Abstract
Hepatitis B virus (HBV) viral load (VL) is used as a biomarker to assess risk of disease progression, and to determine eligibility for treatment. While there is a well recognised association between VL and the expression of the viral e-antigen protein, the distributions of VL at a population level are not well described. We here present cross-sectional, observational HBV VL data from two large population cohorts in the UK and in South Africa, demonstrating a consistent bimodal distribution. The right skewed distribution and low median viral loads are different from the left-skew and higher viraemia in seen in HIV and hepatitis C virus (HCV) cohorts in the same settings. Using longitudinal data, we present evidence for a stable 'set-point' VL in peripheral blood during chronic HBV infection. These results are important to underpin improved understanding of HBV biology, to inform approaches to viral sequencing, and to plan public health interventions.
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Affiliation(s)
- Louise O. Downs
- Department of Infectious Diseases and Microbiology, Oxford Radcliffe Hospital NHS Trust, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Sabeehah Vawda
- Division of Virology, University of the Free State, Bloemfontein, South Africa
| | | | - Katrina A. Lythgoe
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
- Department of Zoology, University Of Oxford, Oxford, UK
| | - Tingyan Wang
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - David A. Smith
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Tongai Maponga
- Department of Virology, University of Stellenbosch, Cape Town, South Africa
| | - Oliver Freeman
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kinga A. Várnai
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jim Davies
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Kerrie Woods
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Eleanor Barnes
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Department of Hepatology, Oxford Radcliffe Hospital NHS Trust, Oxford, UK
| | - Dominique Goedhals
- Division of Virology, University of the Free State, Bloemfontein, South Africa
| | - Philippa C. Matthews
- Department of Infectious Diseases and Microbiology, Oxford Radcliffe Hospital NHS Trust, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
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17
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Arantes I, Ribeiro-Alves M, S. D. de Azevedo S, Delatorre E, Bello G. Few amino acid signatures distinguish HIV-1 subtype B pandemic and non-pandemic strains. PLoS One 2020; 15:e0238995. [PMID: 32960906 PMCID: PMC7508567 DOI: 10.1371/journal.pone.0238995] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 08/27/2020] [Indexed: 11/26/2022] Open
Abstract
The Human Immunodeficiency Virus Type I (HIV-1) subtype B comprises approximately 10% of all HIV infections in the world. The HIV-1 subtype B epidemic comprehends a pandemic variant (named BPANDEMIC) disseminated worldwide and non-pandemic variants (named BCAR) that are mostly restricted to the Caribbean. The goal of this work was the identification of amino acid signatures (AAs) characteristic to the BCAR and BPANDEMIC variants. To this end, we analyzed HIV-1 subtype B full-length (n = 486) and partial (n = 814) genomic sequences from the Americas classified within the BCAR and BPANDEMIC clades and reconstructed the sequences of their most recent common ancestors (MRCA). Analysis of contemporary HIV-1 sequences revealed 13 AAs between BCAR and BPANDEMIC variants (four on Gag, three on Pol, three on Rev, and one in Vif, Vpu, and Tat) of which only two (one on Gag and one on Pol) were traced to the MRCA. All AAs correspond to polymorphic sites located outside essential functional proteins domains, except the AAs in Tat. The absence of stringent AAs inherited from their ancestors between modern BCAR and BPANDEMIC variants support that ecological factors, rather than viral determinants, were the main driving force behind the successful spread of the BPANDEMIC strain.
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Affiliation(s)
- Ighor Arantes
- Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Laboratório de AIDS & Imunologia Molecular, Rio de Janeiro, Brazil
| | - Marcelo Ribeiro-Alves
- Fundação Oswaldo Cruz, Instituto Nacional de Infectologia Evandro Chagas, Laboratório de Pesquisa Clínica em DST-AIDS, Rio de Janeiro, Brazil
| | - Suwellen S. D. de Azevedo
- Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Laboratório de AIDS & Imunologia Molecular, Rio de Janeiro, Brazil
| | - Edson Delatorre
- Universidade Federal do Espírito Santo, Departamento de Biologia, Centro de Ciências Exatas, Naturais e da Saúde, Alegre, Brazil
| | - Gonzalo Bello
- Fundação Oswaldo Cruz, Instituto Oswaldo Cruz, Laboratório de AIDS & Imunologia Molecular, Rio de Janeiro, Brazil
- * E-mail: ,
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18
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Bonsall D, Golubchik T, de Cesare M, Limbada M, Kosloff B, MacIntyre-Cockett G, Hall M, Wymant C, Ansari MA, Abeler-Dörner L, Schaap A, Brown A, Barnes E, Piwowar-Manning E, Eshleman S, Wilson E, Emel L, Hayes R, Fidler S, Ayles H, Bowden R, Fraser C. A Comprehensive Genomics Solution for HIV Surveillance and Clinical Monitoring in Low-Income Settings. J Clin Microbiol 2020; 58:e00382-20. [PMID: 32669382 PMCID: PMC7512176 DOI: 10.1128/jcm.00382-20] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 07/10/2020] [Indexed: 01/01/2023] Open
Abstract
Viral genetic sequencing can be used to monitor the spread of HIV drug resistance, identify appropriate antiretroviral regimes, and characterize transmission dynamics. Despite decreasing costs, next-generation sequencing (NGS) is still prohibitively costly for routine use in generalized HIV epidemics in low- and middle-income countries. Here, we present veSEQ-HIV, a high-throughput, cost-effective NGS sequencing method and computational pipeline tailored specifically to HIV, which can be performed using leftover blood drawn for routine CD4 cell count testing. This method overcomes several major technical challenges that have prevented HIV sequencing from being used routinely in public health efforts; it is fast, robust, and cost-efficient, and generates full genomic sequences of diverse strains of HIV without bias. The complete veSEQ-HIV pipeline provides viral load estimates and quantitative summaries of drug resistance mutations; it also exploits information on within-host viral diversity to construct directed transmission networks. We evaluated the method's performance using 1,620 plasma samples collected from individuals attending 10 large urban clinics in Zambia as part of the HPTN 071-2 study (PopART Phylogenetics). Whole HIV genomes were recovered from 91% of samples with a viral load of >1,000 copies/ml. The cost of the assay (30 GBP per sample) compares favorably with existing VL and HIV genotyping tests, proving an affordable option for combining HIV clinical monitoring with molecular epidemiology and drug resistance surveillance in low-income settings.
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Affiliation(s)
- David Bonsall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Tanya Golubchik
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Mariateresa de Cesare
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Mohammed Limbada
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Barry Kosloff
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - George MacIntyre-Cockett
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - M Azim Ansari
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
| | - Lucie Abeler-Dörner
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Ab Schaap
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Anthony Brown
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
| | - Eleanor Barnes
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
| | | | - Susan Eshleman
- Dept. of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ethan Wilson
- Statistical Centre for HIV/AIDS Research, Fred Hutchinson Cancer Research Centre, Seattle, Washington, USA
| | - Lynda Emel
- Statistical Centre for HIV/AIDS Research, Fred Hutchinson Cancer Research Centre, Seattle, Washington, USA
| | - Richard Hayes
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Sarah Fidler
- Department of Infectious Disease, Imperial College London, Imperial College NIHR BRC, London, United Kingdom
| | - Helen Ayles
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Rory Bowden
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
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19
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Downs LO, Vawda S, Bester PA, Lythgoe KA, Wang T, McNaughton AL, Smith DA, Maponga T, Freeman O, Várnai KA, Davies J, Woods K, Fraser C, Barnes E, Goedhals D, Matthews PC. Bimodal distribution and set point HBV DNA viral loads in chronic infection: retrospective analysis of cohorts from the UK and South Africa. Wellcome Open Res 2020; 5:113. [PMID: 33274299 PMCID: PMC7682492 DOI: 10.12688/wellcomeopenres.15941.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/21/2020] [Indexed: 03/31/2024] Open
Abstract
Hepatitis B virus (HBV) viral load (VL) is used as a biomarker to assess risk of disease progression, and to determine eligibility for treatment. While there is a well recognised association between VL and the expression of the viral e-antigen (HBeAg) protein, the precise determinants and distribution of VL at a population level are not well described. We here report the distribution of HBV VL in two large cross-sectional population cohorts in the UK and in South Africa, demonstrating a consistent bimodal distribution. The right skewed distribution and low median viral loads are significantly different from the left-skew and higher viraemia in seen in comparable HIV and hepatitis C virus (HCV) cohorts. Using longitudinal data, we present evidence for a stable 'set-point' VL in peripheral blood during chronic HBV infection. These results are important to underpin improved understanding of HBV biology and to plan public health interventions.
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Affiliation(s)
- Louise O. Downs
- Department of Infectious Diseases and Microbiology, Oxford Radcliffe Hospital NHS Trust, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Sabeehah Vawda
- Division of Virology, University of the Free State, Bloemfontein, South Africa
| | | | - Katrina A. Lythgoe
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
- Department of Zoology, University Of Oxford, Oxford, UK
| | - Tingyan Wang
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - David A. Smith
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Tongai Maponga
- Department of Virology, University of Stellenbosch, Cape Town, South Africa
| | - Oliver Freeman
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kinga A. Várnai
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jim Davies
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Kerrie Woods
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Eleanor Barnes
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Department of Hepatology, Oxford Radcliffe Hospital NHS Trust, Oxford, UK
| | - Dominique Goedhals
- Division of Virology, University of the Free State, Bloemfontein, South Africa
| | - Philippa C. Matthews
- Department of Infectious Diseases and Microbiology, Oxford Radcliffe Hospital NHS Trust, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- National Institute of Health Research Health Informatics Collaborative, NIHR Oxford Biomedical Research Centre, Oxford, UK
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20
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Kusejko K, Bachmann N, Chaudron SE, Nguyen H, Braun DL, Hampel B, Battegay M, Bernasconi E, Calmy A, Cavassini M, Hoffmann M, Böni J, Yerly S, Klimkait T, Perreau M, Rauch A, Günthard HF, Kouyos RD. A Systematic Phylogenetic Approach to Study the Interaction of HIV-1 With Coinfections, Noncommunicable Diseases, and Opportunistic Diseases. J Infect Dis 2020; 220:244-253. [PMID: 30835292 DOI: 10.1093/infdis/jiz093] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 03/01/2019] [Indexed: 12/21/2022] Open
Abstract
To systematically test whether coinfections spread along the HIV-1 transmission network and whether similarities in HIV-1 genomes predict AIDS-defining illnesses and comorbidities, we analyzed the distribution of these variables on the HIV phylogeny of the densely sampled Swiss HIV Cohort Study. By combining different statistical methods, we could detect, quantify, and explain the clustering of diseases. Infectious conditions such as hepatitis C, but also Kaposi sarcoma, clustered significantly, suggesting transmission of these infections along the HIV-1 transmission network. The clustering of patients with neurocognitive complaints could not be completely explained by the clustering of patients with similar demographic risk factors, which suggests a potential impact of viral genetics. In summary, the consistent and robust signal for coinfections and comorbidities highlights the strong interaction of HIV-1 and other infections and shows the potential of combining phylogenetic methods to identify disease traits that are likely to be related to virus genetic factors.
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Affiliation(s)
- Katharina Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Nadine Bachmann
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Sandra E Chaudron
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Huyen Nguyen
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Dominique L Braun
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Benjamin Hampel
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Manuel Battegay
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Switzerland
| | - Alexandra Calmy
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital, Switzerland
| | - Matthias Hoffmann
- Division of Infectious Diseases, Cantonal Hospital St Gallen, Switzerland
| | - Jürg Böni
- Institute of Medical Virology, University of Zurich, Switzerland
| | - Sabine Yerly
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, Switzerland
| | - Thomas Klimkait
- Molecular Virology, Department of Biomedicine-Petersplatz, University of Basel, Switzerland
| | | | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Switzerland
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21
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Wertheim JO, Oster AM, Switzer WM, Zhang C, Panneer N, Campbell E, Saduvala N, Johnson JA, Heneine W. Natural selection favoring more transmissible HIV detected in United States molecular transmission network. Nat Commun 2019; 10:5788. [PMID: 31857582 PMCID: PMC6923435 DOI: 10.1038/s41467-019-13723-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 11/22/2019] [Indexed: 01/10/2023] Open
Abstract
HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.
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Affiliation(s)
- Joel O Wertheim
- Department of Medicine, University of California, San Diego, CA, USA.
| | - Alexandra M Oster
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - William M Switzer
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Chenhua Zhang
- ICF International, Atlanta, GA, USA
- SciMetrika LLC, Atlanta, GA, USA
| | - Nivedha Panneer
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ellsworth Campbell
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Jeffrey A Johnson
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Walid Heneine
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
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22
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Wirden M, De Oliveira F, Bouvier-Alias M, Lambert-Niclot S, Chaix ML, Raymond S, Si-Mohammed A, Alloui C, André-Garnier E, Bellecave P, Malve B, Mirand A, Pallier C, Poveda JD, Rabenja T, Schneider V, Signori-Schmuck A, Stefic K, Calvez V, Descamps D, Plantier JC, Marcelin AG, Visseaux B. New HIV-1 circulating recombinant form 94: from phylogenetic detection of a large transmission cluster to prevention in the age of geosocial-networking apps in France, 2013 to 2017. Euro Surveill 2019; 24:1800658. [PMID: 31576801 PMCID: PMC6774227 DOI: 10.2807/1560-7917.es.2019.24.39.1800658] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
BackgroundEnding the HIV pandemic must involve new tools to rapidly identify and control local outbreaks and prevent the emergence of recombinant strains with epidemiological advantages.AimThis observational study aimed to investigate in France a cluster of HIV-1 cases related to a new circulating recombinant form (CRF). The confirmation this CRF's novelty as well as measures to control its spread are presented.MethodsPhylogenetic analyses of HIV sequences routinely generated for drug resistance genotyping before 2018 in French laboratories were employed to detect the transmission chain. The CRF involved was characterised by almost full-length viral sequencing for six cases. Cases' clinical data were reviewed. Where possible, epidemiological information was collected with a questionnaire.ResultsThe transmission cluster comprised 49 cases, mostly diagnosed in 2016-2017 (n = 37). All were infected with a new CRF, CRF94_cpx. The molecular proximity of this CRF to X4 strains and the high median viraemia, exceeding 5.0 log10 copies/mL, at diagnosis, even in chronic infection, raise concerns of enhanced virulence. Overall, 41 cases were diagnosed in the Ile-de-France region and 45 were men who have sex with men. Among 24 cases with available information, 20 reported finding partners through a geosocial networking app. Prevention activities in the area and population affected were undertaken.ConclusionWe advocate the systematic use of routinely generated HIV molecular data by a dedicated reactive network, to improve and accelerate targeted prevention interventions. Geosocial networking apps can play a role in the spread of outbreaks, but could also deliver local targeted preventive alerts.
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Affiliation(s)
- Marc Wirden
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié Salpêtrière, Laboratoire de virologie, Paris, France
| | - Fabienne De Oliveira
- Normandie Université, UNIROUEN, EA2656 GRAM, CHU de Rouen, Laboratoire de virologie associé au CNR VIH, Rouen, France
| | | | | | - Marie-Laure Chaix
- AP-HP, Hôpital Saint-Louis, Laboratoire de virologie, INSERM U944, Paris, France
| | | | | | - Chakib Alloui
- Laboratoire de virologie, Hôpital Avicenne, Bobigny, France
| | | | | | - Brice Malve
- Laboratoire de virologie CHU de Nancy, Nancy, France
| | - Audrey Mirand
- Laboratoire de virologie CHU de Clermont-Ferrand, Clermont-Ferrand, France
| | - Coralie Pallier
- Laboratoire de virologie, Hôpital P. Brousse, Villejuif, France
| | | | - Theresa Rabenja
- Laboratoire du Grand Hôpital de l’Est Francilien, Jossigny, France
| | | | | | - Karl Stefic
- Laboratoire de virologie CHU de Tours, Tours, France
| | - Vincent Calvez
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié Salpêtrière, Laboratoire de virologie, Paris, France
| | - Diane Descamps
- Laboratoire de virologie, AP-HP, Hopital Bichat Claude Bernard, Univ Paris-Diderot, INSERM, IAME, CNR VIH, Paris, France
| | - Jean-Christophe Plantier
- Normandie Université, UNIROUEN, EA2656 GRAM, CHU de Rouen, Laboratoire de virologie associé au CNR VIH, Rouen, France
| | - Anne-Genevieve Marcelin
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, AP-HP, Hôpital Pitié Salpêtrière, Laboratoire de virologie, Paris, France
| | - Benoit Visseaux
- Laboratoire de virologie, AP-HP, Hopital Bichat Claude Bernard, Univ Paris-Diderot, INSERM, IAME, CNR VIH, Paris, France
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23
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Mitov V, Bartoszek K, Stadler T. Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models. Proc Natl Acad Sci U S A 2019; 116:16921-16926. [PMID: 31375629 PMCID: PMC6708313 DOI: 10.1073/pnas.1813823116] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Phylogenetic comparative methods are widely used to understand and quantify the evolution of phenotypic traits, based on phylogenetic trees and trait measurements of extant species. Such analyses depend crucially on the underlying model. Gaussian phylogenetic models like Brownian motion and Ornstein-Uhlenbeck processes are the workhorses of modeling continuous-trait evolution. However, these models fit poorly to big trees, because they neglect the heterogeneity of the evolutionary process in different lineages of the tree. Previous works have addressed this issue by introducing shifts in the evolutionary model occurring at inferred points in the tree. However, for computational reasons, in all current implementations, these shifts are "intramodel," meaning that they allow jumps in 1 or 2 model parameters, keeping all other parameters "global" for the entire tree. There is no biological reason to restrict a shift to a single model parameter or, even, to a single type of model. Mixed Gaussian phylogenetic models (MGPMs) incorporate the idea of jointly inferring different types of Gaussian models associated with different parts of the tree. Here, we propose an approximate maximum-likelihood method for fitting MGPMs to comparative data comprising possibly incomplete measurements for several traits from extant and extinct phylogenetically linked species. We applied the method to the largest published tree of mammal species with body- and brain-mass measurements, showing strong statistical support for an MGPM with 12 distinct evolutionary regimes. Based on this result, we state a hypothesis for the evolution of the brain-body-mass allometry over the past 160 million y.
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Affiliation(s)
- Venelin Mitov
- Computational Evolution Group, Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland;
- Computational Evolution Group, Swiss Institute of Bioinformatics (SIB), 4058 Basel, Switzerland
| | - Krzysztof Bartoszek
- Division of Statistics and Machine Learning, Department of Computer and Information Science, Linköping University, 58183 Linköping, Sweden
| | - Tanja Stadler
- Computational Evolution Group, Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
- Computational Evolution Group, Swiss Institute of Bioinformatics (SIB), 4058 Basel, Switzerland
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24
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Bertels F, Marzel A, Leventhal G, Mitov V, Fellay J, Günthard HF, Böni J, Yerly S, Klimkait T, Aubert V, Battegay M, Rauch A, Cavassini M, Calmy A, Bernasconi E, Schmid P, Scherrer AU, Müller V, Bonhoeffer S, Kouyos R, Regoes RR. Dissecting HIV Virulence: Heritability of Setpoint Viral Load, CD4+ T-Cell Decline, and Per-Parasite Pathogenicity. Mol Biol Evol 2019; 35:27-37. [PMID: 29029206 PMCID: PMC5850767 DOI: 10.1093/molbev/msx246] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Pathogen strains may differ in virulence because they attain different loads in their hosts, or because they induce different disease-causing mechanisms independent of their load. In evolutionary ecology, the latter is referred to as “per-parasite pathogenicity”. Using viral load and CD4+ T-cell measures from 2014 HIV-1 subtype B-infected individuals enrolled in the Swiss HIV Cohort Study, we investigated if virulence—measured as the rate of decline of CD4+ T cells—and per-parasite pathogenicity are heritable from donor to recipient. We estimated heritability by donor–recipient regressions applied to 196 previously identified transmission pairs, and by phylogenetic mixed models applied to a phylogenetic tree inferred from HIV pol sequences. Regressing the CD4+ T-cell declines and per-parasite pathogenicities of the transmission pairs did not yield heritability estimates significantly different from zero. With the phylogenetic mixed model, however, our best estimate for the heritability of the CD4+ T-cell decline is 17% (5–30%), and that of the per-parasite pathogenicity is 17% (4–29%). Further, we confirm that the set-point viral load is heritable, and estimate a heritability of 29% (12–46%). Interestingly, the pattern of evolution of all these traits differs significantly from neutrality, and is most consistent with stabilizing selection for the set-point viral load, and with directional selection for the CD4+ T-cell decline and the per-parasite pathogenicity. Our analysis shows that the viral genotype affects virulence mainly by modulating the per-parasite pathogenicity, while the indirect effect via the set-point viral load is minor.
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Affiliation(s)
- Frederic Bertels
- Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
| | - Alex Marzel
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Venelin Mitov
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Jacques Fellay
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Jürg Böni
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Sabine Yerly
- Division of Infectious Diseases, Laboratory of Virology, Geneva University Hospital, Geneva, Switzerland
| | - Thomas Klimkait
- Molecular Virology, Department of Biomedicine - Petersplatz, University of Basel, Basel, Switzerland
| | - Vincent Aubert
- Division of Immunology and Allergy, University Hospital Lausanne, Lausanne, Switzerland
| | - Manuel Battegay
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Berne University Hospital and University of Berne, Berne, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, University Hospital Lausanne, Lausanne, Switzerland
| | - Alexandra Calmy
- HIV/AIDS Unit, Infectious Disease Service, Geneva University Hospital, Geneva, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Patrick Schmid
- Division of Infectious Diseases, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Alexandra U Scherrer
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Viktor Müller
- Institute of Biology, Eötvös Loránd University, Budapest, Hungary.,Evolutionary Systems Research Group, MTA Centre for Ecological Research, Tihany, Hungary
| | | | - Roger Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Roland R Regoes
- Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
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25
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Abstract
How virulence evolves after a virus jumps to a new host species is central to disease emergence. Our current understanding of virulence evolution is based on insights drawn from two perspectives that have developed largely independently: long-standing evolutionary theory based on limited real data examples that often lack a genomic basis, and experimental studies of virulence-determining mutations using cell culture or animal models. A more comprehensive understanding of virulence mutations and their evolution can be achieved by bridging the gap between these two research pathways through the phylogenomic analysis of virus genome sequence data as a guide to experimental study.
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Affiliation(s)
- Jemma L Geoghegan
- Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Edward C Holmes
- Marie Bashir Institute for Infectious Diseases and Biosecurity, Charles Perkins Centre, School of Life and Environmental Sciences and Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia.
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26
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Wymant C, Blanquart F, Golubchik T, Gall A, Bakker M, Bezemer D, Croucher NJ, Hall M, Hillebregt M, Ong SH, Ratmann O, Albert J, Bannert N, Fellay J, Fransen K, Gourlay A, Grabowski MK, Gunsenheimer-Bartmeyer B, Günthard HF, Kivelä P, Kouyos R, Laeyendecker O, Liitsola K, Meyer L, Porter K, Ristola M, van Sighem A, Berkhout B, Cornelissen M, Kellam P, Reiss P, Fraser C. Easy and accurate reconstruction of whole HIV genomes from short-read sequence data with shiver. Virus Evol 2018; 4:vey007. [PMID: 29876136 PMCID: PMC5961307 DOI: 10.1093/ve/vey007] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Studying the evolution of viruses and their molecular epidemiology relies on accurate viral sequence data, so that small differences between similar viruses can be meaningfully interpreted. Despite its higher throughput and more detailed minority variant data, next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of large between- and within-host diversity, including frequent indels, may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to pre-process reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We used shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read whole-genome data produced with the Illumina platform, for sixty-five existing publicly available samples and fifty new samples. We show the systematic superiority of mapping to shiver's constructed reference compared with mapping the same reads to the closest of 3,249 real references: median values of 13 bases called differently and more accurately, 0 bases called differently and less accurately, and 205 bases of missing sequence recovered. We also successfully applied shiver to whole-genome samples of Hepatitis C Virus and Respiratory Syncytial Virus. shiver is publicly available from https://github.com/ChrisHIV/shiver.
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Affiliation(s)
- Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - François Blanquart
- Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Tanya Golubchik
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Astrid Gall
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK.,Virus Genomics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Margreet Bakker
- Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center of the University of Amsterdam, Amsterdam, The Netherlands
| | | | - Nicholas J Croucher
- Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | | | - Swee Hoe Ong
- Virus Genomics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Oliver Ratmann
- Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.,Department of Mathematics, Imperial College London, London, UK
| | - Jan Albert
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden
| | - Norbert Bannert
- Division for HIV and Other Retroviruses, Robert Koch Institute, Berlin, Germany
| | - Jacques Fellay
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Katrien Fransen
- HIV/STI Reference Laboratory, Department of Clinical Science, WHO Collaborating Centre, Institute of Tropical Medicine, Antwerpen, Belgium
| | - Annabelle Gourlay
- Institute for Global Health, University College London, London, UK.,Department of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - M Kate Grabowski
- Department of Pathology, John Hopkins University, Baltimore, MD, USA
| | | | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Pia Kivelä
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | - Roger Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Kirsi Liitsola
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | - Laurence Meyer
- INSERM CESP U1018, Université Paris Sud, Université Paris Saclay, APHP, Service de Santé Publique, Hôpital de Bicêtre, Le Kremlin-Bicêtre, France
| | - Kholoud Porter
- Institute for Global Health, University College London, London, UK
| | - Matti Ristola
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | | | - Ben Berkhout
- Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center of the University of Amsterdam, Amsterdam, The Netherlands
| | - Marion Cornelissen
- Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center of the University of Amsterdam, Amsterdam, The Netherlands
| | - Paul Kellam
- Kymab Ltd, Cambridge, UK.,Division of Infectious Diseases, Department of Medicine, Imperial College London, London, UK
| | - Peter Reiss
- Stichting HIV Monitoring, Amsterdam, The Netherlands.,Department of Global Health, Academic Medical Center and Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
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27
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van der Kuyl AC, Vink M, Zorgdrager F, Bakker M, Wymant C, Hall M, Gall A, Blanquart F, Berkhout B, Fraser C, Cornelissen M. The evolution of subtype B HIV-1 tat in the Netherlands during 1985-2012. Virus Res 2018; 250:51-64. [PMID: 29654800 DOI: 10.1016/j.virusres.2018.04.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Revised: 04/05/2018] [Accepted: 04/05/2018] [Indexed: 12/18/2022]
Abstract
For the production of viral genomic RNA, HIV-1 is dependent on an early viral protein, Tat, which is required for high-level transcription. The quantity of viral RNA detectable in blood of HIV-1 infected individuals varies dramatically, and a factor involved could be the efficiency of Tat protein variants to stimulate RNA transcription. HIV-1 virulence, measured by set-point viral load, has been observed to increase over time in the Netherlands and elsewhere. Investigation of tat gene evolution in clinical isolates could discover a role of Tat in this changing virulence. A dataset of 291 Dutch HIV-1 subtype B tat genes, derived from full-length HIV-1 genome sequences from samples obtained between 1985-2012, was used to analyse the evolution of Tat. Twenty-two patient-derived tat genes, and the control TatHXB2 were analysed for their capacity to stimulate expression of an LTR-luciferase reporter gene construct in diverse cell lines, as well as for their ability to complement a tat-defective HIV-1LAI clone. Analysis of 291 historical tat sequences from the Netherlands showed ample amino acid (aa) variation between isolates, although no specific mutations were selected for over time. Of note, however, the encoded protein varied its length over the years through the loss or gain of stop codons in the second exon. In transmission clusters, a selection against the shorter Tat86 ORF was apparent in favour of the more common Tat101 version, likely due to negative selection against Tat86 itself, although random drift, transmission bottlenecks, or linkage to other variants could also explain the observation. There was no correlation between Tat length and set-point viral load; however, the number of non-intermediate variants in our study was small. In addition, variation in the length of Tat did not significantly change its capacity to stimulate transcription. From 1985 till 2012, variation in the length of the HIV-1 subtype B tat gene is increasingly found in the Dutch epidemic. However, as Tat proteins did not differ significantly in their capacity to stimulate transcription elongation in vitro, the increased HIV-1 virulence seen in recent years could not be linked to an evolving viral Tat protein.
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Affiliation(s)
- Antoinette C van der Kuyl
- Laboratory of Experimental Virology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands.
| | - Monique Vink
- Laboratory of Experimental Virology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| | - Fokla Zorgdrager
- Laboratory of Experimental Virology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| | - Margreet Bakker
- Laboratory of Experimental Virology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| | - Chris Wymant
- Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, W21PG, United Kingdom; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Astrid Gall
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - François Blanquart
- Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, W21PG, United Kingdom; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Ben Berkhout
- Laboratory of Experimental Virology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| | - Christophe Fraser
- Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, W21PG, United Kingdom; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Marion Cornelissen
- Laboratory of Experimental Virology, Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
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28
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Casado C, Marrero-Hernández S, Márquez-Arce D, Pernas M, Marfil S, Borràs-Grañana F, Olivares I, Cabrera-Rodríguez R, Valera MS, de Armas-Rillo L, Lemey P, Blanco J, Valenzuela-Fernández A, Lopez-Galíndez C. Viral Characteristics Associated with the Clinical Nonprogressor Phenotype Are Inherited by Viruses from a Cluster of HIV-1 Elite Controllers. mBio 2018; 9:e02338-17. [PMID: 29636433 PMCID: PMC5893881 DOI: 10.1128/mbio.02338-17] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 03/09/2018] [Indexed: 11/20/2022] Open
Abstract
A small group of HIV-1-infected individuals, called long-term nonprogressors (LTNPs), and in particular a subgroup of LTNPs, elite controllers (LTNP-ECs), display permanent control of viral replication and lack of clinical progression. This control is the result of a complex interaction of host, immune, and viral factors. We identified, by phylogenetic analysis, a cluster of LTNP-ECs infected with very similar low-replication HIV-1 viruses, suggesting the contribution of common viral features to the clinical LTNP-EC phenotype. HIV-1 envelope (Env) glycoprotein mediates signaling and promotes HIV-1 fusion, entry, and infection, being a key factor of viral fitness in vitro, cytopathicity, and infection progression in vivo Therefore, we isolated full-length env genes from viruses of these patients and from chronically infected control individuals. Functional characterization of the initial events of the viral infection showed that Envs from the LTNP-ECs were ineffective in the binding to CD4 and in the key triggering of actin/tubulin-cytoskeleton modifications compared to Envs from chronic patients. The viral properties of the cluster viruses result in a defective viral fusion, entry, and infection, and these properties were inherited by every virus of the cluster. Therefore, inefficient HIV-1 Env functions and signaling defects may contribute to the low viral replication capacity and transmissibility of the cluster viruses, suggesting a direct role in the LTNP-EC phenotype of these individuals. These results highlight the important role of viral characteristics in the LTNP-EC clinical phenotype. These Env viral properties were common to all the cluster viruses and thus support the heritability of the viral characteristics.IMPORTANCE HIV-1 long-term nonprogressor elite controller patients, due to their permanent control of viral replication, have been the object of numerous studies to identify the factors responsible for this clinical phenotype. In this work, we analyzed the viral characteristics of the envelopes of viruses from a phylogenetic cluster of LTNP-EC patients. These envelopes showed ineffective binding to CD4 and the subsequent signaling activity to modify actin/tubulin cytoskeletons, which result in low fusion and deficient entry and infection capacities. These Env viral characteristics could explain the nonprogressor clinical phenotype of these patients. In addition, these inefficient env viral properties were present in all viruses of the cluster, supporting the heritability of the viral phenotype.
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Affiliation(s)
- Concepción Casado
- Unidad de Virologia Molecular, Laboratorio de Referencia e Investigación en Retrovirus, Centro Nacional de Microbiología (CNM), Instituto de Salud Carlos IIII, Majadahonda, Madrid, Spain
| | - Sara Marrero-Hernández
- Laboratorio de Inmunología Celular y Viral, Unidad de Virología IUETSPC, Unidad de Farmacología, Sección de Medicina, Facultad de Ciencias de la Salud, Universidad de La Laguna (ULL), Tenerife, Spain
| | - Daniel Márquez-Arce
- Laboratorio de Inmunología Celular y Viral, Unidad de Virología IUETSPC, Unidad de Farmacología, Sección de Medicina, Facultad de Ciencias de la Salud, Universidad de La Laguna (ULL), Tenerife, Spain
| | - María Pernas
- Unidad de Virologia Molecular, Laboratorio de Referencia e Investigación en Retrovirus, Centro Nacional de Microbiología (CNM), Instituto de Salud Carlos IIII, Majadahonda, Madrid, Spain
| | - Sílvia Marfil
- Institut de Recerca de la Sida IrsiCaixa, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol (IGTP), Badalona, Spain
| | - Ferran Borràs-Grañana
- Institut de Recerca de la Sida IrsiCaixa, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol (IGTP), Badalona, Spain
| | - Isabel Olivares
- Unidad de Virologia Molecular, Laboratorio de Referencia e Investigación en Retrovirus, Centro Nacional de Microbiología (CNM), Instituto de Salud Carlos IIII, Majadahonda, Madrid, Spain
| | - Romina Cabrera-Rodríguez
- Laboratorio de Inmunología Celular y Viral, Unidad de Virología IUETSPC, Unidad de Farmacología, Sección de Medicina, Facultad de Ciencias de la Salud, Universidad de La Laguna (ULL), Tenerife, Spain
| | - María-Soledad Valera
- Laboratorio de Inmunología Celular y Viral, Unidad de Virología IUETSPC, Unidad de Farmacología, Sección de Medicina, Facultad de Ciencias de la Salud, Universidad de La Laguna (ULL), Tenerife, Spain
| | - Laura de Armas-Rillo
- Laboratorio de Inmunología Celular y Viral, Unidad de Virología IUETSPC, Unidad de Farmacología, Sección de Medicina, Facultad de Ciencias de la Salud, Universidad de La Laguna (ULL), Tenerife, Spain
| | - Philippe Lemey
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, University of Leuven, Leuven, Belgium
| | - Julià Blanco
- Institut de Recerca de la Sida IrsiCaixa, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol (IGTP), Badalona, Spain
- Universitat de Vic, Universitat Central de Catalunya, UVIC, Vic, Spain
| | - Agustín Valenzuela-Fernández
- Laboratorio de Inmunología Celular y Viral, Unidad de Virología IUETSPC, Unidad de Farmacología, Sección de Medicina, Facultad de Ciencias de la Salud, Universidad de La Laguna (ULL), Tenerife, Spain
| | - Cecilio Lopez-Galíndez
- Unidad de Virologia Molecular, Laboratorio de Referencia e Investigación en Retrovirus, Centro Nacional de Microbiología (CNM), Instituto de Salud Carlos IIII, Majadahonda, Madrid, Spain
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Abstract
The continual emergence of new pathogens and the increased spread of antibiotic resistance in bacterial populations remind us that microbes are living entities that evolve at rates that impact public health interventions. Following the historical thread of the works of Pasteur and Darwin shows how reconciling clinical microbiology, ecology, and evolution can be instrumental to understanding pathology, developing new therapies, and prolonging the efficiency of existing ones.
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Affiliation(s)
- Samuel Alizon
- Laboratoire MIVEGEC (UMR CNRS 5290, UR IRD 224, UM), Montpellier, France
- * E-mail:
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30
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Abstract
Pathogen traits, such as the virulence of an infection, can vary significantly between patients. A major challenge is to measure the extent to which genetic differences between infecting strains explain the observed variation of the trait. This is quantified by the trait’s broad-sense heritability, H2. A recent discrepancy between estimates of the heritability of HIV-virulence has opened a debate on the estimators’ accuracy. Here, we show that the discrepancy originates from model limitations and important lifecycle differences between sexually reproducing organisms and transmittable pathogens. In particular, current quantitative genetics methods, such as donor–recipient regression of surveyed serodiscordant couples and the phylogenetic mixed model (PMM), are prone to underestimate H2, because they neglect or do not fit to the loss of resemblance between transmission partners caused by within-host evolution. In a phylogenetic analysis of 8,483 HIV patients from the United Kingdom, we show that the phenotypic correlation between transmission partners decays with the amount of within-host evolution of the virus. We reproduce this pattern in toy-model simulations and show that a phylogenetic Ornstein–Uhlenbeck model (POUMM) outperforms the PMM in capturing this correlation pattern and in quantifying H2. In particular, we show that POUMM outperforms PMM even in simulations without selection—as it captures the mentioned correlation pattern—which has not been appreciated until now. By cross-validating the POUMM estimates with ANOVA on closest phylogenetic pairs, we obtain H2 ≈ 0.2, meaning ∼20% of the variation in HIV-virulence is explained by the virus genome both for European and African data.
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Affiliation(s)
- Venelin Mitov
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.,Swiss Institute of Bioinformatics, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.,Swiss Institute of Bioinformatics, Switzerland
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31
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Correction: Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe. PLoS Biol 2017; 15:e1002608. [PMID: 28704367 PMCID: PMC5509086 DOI: 10.1371/journal.pbio.1002608] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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