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Viral Diversity Based on Next-Generation Sequencing of HIV-1 Provides Precise Estimates of Infection Recency and Time Since Infection.
Carlisle, Louisa A; Turk, Teja; Kusejko, Katharina; Metzner, Karin J; Leemann, Christine; Schenkel, Corinne D; Bachmann, Nadine; Posada, Susana; Beerenwinkel, Niko; Böni, Jürg; Yerly, Sabine; Klimkait, Thomas; Perreau, Matthieu; Braun, Dominique L; Rauch, Andri; Calmy, Alexandra; Cavassini, Matthias; Battegay, Manuel; Vernazza, Pietro; Bernasconi, Enos; Günthard, Huldrych F; Kouyos, Roger D.
  • Carlisle LA; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
  • Turk T; Institute of Medical Virology, University of Zurich, Zurich.
  • Kusejko K; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
  • Metzner KJ; Institute of Medical Virology, University of Zurich, Zurich.
  • Leemann C; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
  • Schenkel CD; Institute of Medical Virology, University of Zurich, Zurich.
  • Bachmann N; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
  • Posada S; Institute of Medical Virology, University of Zurich, Zurich.
  • Beerenwinkel N; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
  • Böni J; Institute of Medical Virology, University of Zurich, Zurich.
  • Yerly S; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
  • Klimkait T; Institute of Medical Virology, University of Zurich, Zurich.
  • Perreau M; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
  • Braun DL; Institute of Medical Virology, University of Zurich, Zurich.
  • Rauch A; Department of Biosystems Science and Engineering, ETH Zurich.
  • Calmy A; SIB Swiss Institute of Bioinformatics, University of Basel, Basel.
  • Cavassini M; Department of Biosystems Science and Engineering, ETH Zurich.
  • Battegay M; SIB Swiss Institute of Bioinformatics, University of Basel, Basel.
  • Vernazza P; Institute of Medical Virology, University of Zurich, Zurich.
  • Bernasconi E; Swiss National Center for Retroviruses, University of Zurich, Zurich.
  • Günthard HF; Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, Geneva.
  • Kouyos RD; Molecular Virology, Department of Biomedicine-Petersplatz, University of Basel, Basel.
J Infect Dis ; 220(2): 254-265, 2019 06 19.
Article en En | MEDLINE | ID: mdl-30835266
BACKGROUND: Human immunodeficiency virus type 1 (HIV-1) genetic diversity increases over the course of infection and can be used to infer the time since infection and, consequently, infection recency, which are crucial for HIV-1 surveillance and the understanding of viral pathogenesis. METHODS: We considered 313 HIV-infected individuals for whom reliable estimates of infection dates and next-generation sequencing (NGS)-derived nucleotide frequency data were available. Fractions of ambiguous nucleotides, obtained by population sequencing, were available for 207 samples. We assessed whether the average pairwise diversity calculated using NGS sequences provided a more exact prediction of the time since infection and classification of infection recency (<1 year after infection), compared with the fraction of ambiguous nucleotides. RESULTS: NGS-derived average pairwise diversity classified an infection as recent with a sensitivity of 88% and a specificity of 85%. When considering only the 207 samples for which fractions of ambiguous nucleotides were available, the NGS-derived average pairwise diversity exhibited a higher sensitivity (90% vs 78%) and specificity (95% vs 67%) than the fraction of ambiguous nucleotides. Additionally, the average pairwise diversity could be used to estimate the time since infection with a mean absolute error of 0.84 years, compared with 1.03 years for the fraction of ambiguous nucleotides. CONCLUSIONS: Viral diversity based on NGS data is more precise than that based on population sequencing in its ability to predict infection recency and provides an estimated time since infection that has a mean absolute error of <1 year.
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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2019 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2019 Tipo del documento: Article