4.6 Article

Examining the dynamics of Epstein-Barr virus shedding in the tonsils and the impact of HIV-1 coinfection on daily saliva viral loads

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PLOS COMPUTATIONAL BIOLOGY
卷 17, 期 6, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1009072

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资金

  1. Natural Sciences and Engineering Research Council of Canada [RGPIN-2015-03611]
  2. Emory University (Quantitative Theory and Methods Initiative)
  3. Canadian Institutes of Health Research
  4. Fred Hutchinson Cancer Research Center (Joel Meyers Infectious Disease Scholarship Grant)
  5. Fred Hutchinson Cancer Research Center (Early Detection Initiative)
  6. Doris Duke Charitable Foundation
  7. National Institutes of Health [P30 CA015704, K23 AI54162, K23 AI079394, P30 AI027757, K24 AI071113, PO1 AI030731]
  8. WestGrid
  9. Compute Canada

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Epstein-Barr virus (EBV) is a major cause of cancer transmitted through saliva, particularly in individuals living with HIV/AIDS. A study in Uganda found that HIV-1 coinfected individuals had a higher risk of EBV detection in saliva and higher viral loads compared to those without HIV-1. Mathematical modeling revealed that HIV-1 coinfected individuals had higher rates of B cell reactivation, potentially explaining the more frequent detection of EBV in their saliva.
Epstein-Barr virus (EBV) is transmitted by saliva and is a major cause of cancer, particularly in people living with HIV/AIDS. Here, we describe the frequency and quantity of EBV detection in the saliva of Ugandan adults with and without HIV-1 infection and use these data to develop a novel mathematical model of EBV infection in the tonsils. Eligible cohort participants were not taking antiviral medications, and those with HIV-1 infection had a CD4 count >200 cells/mm(3). Over a 4-week period, participants provided daily oral swabs that we analysed for the presence and quantity of EBV. Compared with HIV-1 uninfected participants, HIV-1 coinfected participants had an increased risk of EBV detection in their saliva (IRR = 1.27, 95% CI = 1.10-1.47) and higher viral loads in positive samples. We used these data to develop a stochastic, mechanistic mathematical model that describes the dynamics of EBV, infected cells, and immune response within the tonsillar epithelium to analyse potential factors that may cause EBV infection to be more severe in HIV-1 coinfected participants. The model, fit using Approximate Bayesian Computation, showed high fidelity to daily oral shedding data and matched key summary statistics. When evaluating how model parameters differed among participants with and without HIV-1 coinfection, results suggest HIV-1 coinfected individuals have higher rates of B cell reactivation, which can seed new infection in the tonsils and lower rates of an EBV-specific immune response. Subsequently, both these traits may explain higher and more frequent EBV detection in the saliva of HIV-1 coinfected individuals.

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