A transmission-virulence evolutionary trade-off explains attenuation of HIV-1 in Uganda

  1. François Blanquart  Is a corresponding author
  2. Mary Kate Grabowski
  3. Joshua Herbeck
  4. Fred Nalugoda
  5. David Serwadda
  6. Michael A Eller
  7. Merlin L Robb
  8. Ronald Gray
  9. Godfrey Kigozi
  10. Oliver Laeyendecker
  11. Katrina A Lythgoe
  12. Gertrude Nakigozi
  13. Thomas C Quinn
  14. Steven J Reynolds
  15. Maria J Wawer
  16. Christophe Fraser
  1. Imperial College London, United Kingdom
  2. Johns Hopkins University, United States
  3. University of Washington, United States
  4. Rakai Health Sciences Program, Uganda
  5. Walter Reed Army Institute of Research, United States
  6. National Institutes of Health, United States

Abstract

Evolutionary theory hypothesizes that intermediate virulence maximizes pathogen fitness as a result of a trade-off between virulence and transmission, but empirical evidence remains scarce. We bridge this gap using data from a large and long-standing HIV-1 prospective cohort, in Uganda. We use an epidemiological-evolutionary model parameterised with this data to derive evolutionary predictions based on analysis and detailed individual-based simulations. We robustly predict stabilising selection towards a low level of virulence, and rapid attenuation of the virus. Accordingly, set-point viral load, the most common measure of virulence, has declined in the last 20 years. Our model also predicts that subtype A is slowly outcompeting subtype D, with both subtypes becoming less virulent, as observed in the data. Reduction of set-point viral loads should have resulted in a 20% reduction in incidence, and a three years extension of untreated asymptomatic infection, increasing opportunities for timely treatment of infected individuals.

Data availability

The following data sets were generated

Article and author information

Author details

  1. François Blanquart

    MRC Centre for Outbreak Analysis and Modelling, School of Public Health, Imperial College London, London, United Kingdom
    For correspondence
    f.blanquart@imperial.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0591-2466
  2. Mary Kate Grabowski

    Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Joshua Herbeck

    International Clinical Research Center, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4577-7406
  4. Fred Nalugoda

    Rakai Health Sciences Program, Entebbe, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  5. David Serwadda

    Rakai Health Sciences Program, Entebbe, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  6. Michael A Eller

    U.S. Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Merlin L Robb

    U.S. Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Ronald Gray

    Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Godfrey Kigozi

    Rakai Health Sciences Program, Entebbe, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  10. Oliver Laeyendecker

    Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Katrina A Lythgoe

    MRC Centre for Outbreak Analysis and Modelling, School of Public Health, Imperial College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  12. Gertrude Nakigozi

    Rakai Health Sciences Program, Entebbe, Uganda
    Competing interests
    The authors declare that no competing interests exist.
  13. Thomas C Quinn

    Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Steven J Reynolds

    Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Maria J Wawer

    Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Christophe Fraser

    MRC Centre for Outbreak Analysis and Modelling, School of Public Health, Imperial College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

Funding

European Commission (Intra European Fellowship 657768)

  • François Blanquart

World Bank Group

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

Henry M. Jackson Foundation (W81XWH-07-2-0067)

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

U.S. Department of Defense (W81XWH-07-2-0067)

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

National Institutes of Health (R01AI108490; P30AI027757)

  • Joshua Herbeck

European Research Council (PBDR-339251)

  • Christophe Fraser

National Institute of Allergy and Infectious Diseases (R01 Al 29314; R01 AI34826; UO1 AI11171-01-02)

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

National Institute of Child Health and Human Development (5P30 HD 06268)

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

John E. Fogarty Foundation for Persons with Intellectual and Developmental Disabilities (5D43TW00010)

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

John Snow Inc. (5024-30)

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

Pfizer (5024-30)

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

Rockefeller Foundation

  • Mary Kate Grabowski
  • Fred Nalugoda
  • David Serwadda
  • Michael A Eller
  • Merlin L Robb
  • Ronald Gray
  • Godfrey Kigozi
  • Oliver Laeyendecker
  • Gertrude Nakigozi
  • Thomas C Quinn
  • Steven J Reynolds
  • Maria J Wawer

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Informed consent was obtained from all the participants in the Rakai Community Cohort Study.The Scientific and Ethics Committee of the Uganda Virus Research Institute (UVRI) of the Ministry of Health provides the Institutional Review Board approval and monitoring of all Rakai research.

Reviewing Editor

  1. Richard A Neher, Max Planck Institute for Developmental Biology, Germany

Publication history

  1. Received: August 10, 2016
  2. Accepted: November 1, 2016
  3. Accepted Manuscript published: November 5, 2016 (version 1)
  4. Accepted Manuscript updated: November 8, 2016 (version 2)
  5. Version of Record published: November 18, 2016 (version 3)

Copyright

© 2016, Blanquart et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. François Blanquart
  2. Mary Kate Grabowski
  3. Joshua Herbeck
  4. Fred Nalugoda
  5. David Serwadda
  6. Michael A Eller
  7. Merlin L Robb
  8. Ronald Gray
  9. Godfrey Kigozi
  10. Oliver Laeyendecker
  11. Katrina A Lythgoe
  12. Gertrude Nakigozi
  13. Thomas C Quinn
  14. Steven J Reynolds
  15. Maria J Wawer
  16. Christophe Fraser
(2016)
A transmission-virulence evolutionary trade-off explains attenuation of HIV-1 in Uganda
eLife 5:e20492.
https://doi.org/10.7554/eLife.20492

Further reading

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    Methods: In this study, we analyzed data from 44,709 non-diabetic U.K. Biobank participants aged 40-69, predicting the risk of T2D onset within a selected timeframe (mean of 7.3 years with a standard deviation of 2.3 years). We started with 798 features that we identified as potential predictors for T2D onset. We first analyzed the data using gradient boosting decision trees, survival analysis, and logistic regression methods. We devised one non-laboratory model accessible to the general population and one more precise yet simple model that utilizes laboratory tests. We simplified both models to an accessible scorecard form, tested the models on normoglycemic and prediabetes sub cohorts, and compared the results to the results of the general cohort. We established the non-laboratory model using the following covariates: sex, age, weight, height, waist size, hip circumference, waist-to-hip Ratio (WHR), and Body-Mass Index (BMI). For the laboratory model, we used age and sex together with four common blood tests: HDL (high-density lipoprotein), gamma-glutamyl transferase, glycated hemoglobin, and triglycerides. As an external validation dataset, we used the electronic medical record database of Clalit Health Services.

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    Conclusions: The four blood tests and anthropometric models outperformed the commonly used non-laboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset.

    Funding: No Funders. The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.

    1. Epidemiology and Global Health
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    To assess the effect of the COVID-19 pandemic on performance indicators in the population-based breast cancer screening program of Parc de Salut Mar (PSMAR), Barcelona, Spain.

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    We conducted a before-and-after, study to evaluate participation, recall, false positives, the cancer detection rate, and cancer characteristics in our screening population from March 2020 to March 2021 compared with the four previous rounds (2012–2019). Using multilevel logistic regression models, we estimated the adjusted odds ratios (aORs) of each of the performance indicators for the COVID-19 period, controlling by type of screening (prevalent or incident), socioeconomic index, family history of breast cancer, and menopausal status. We analyzed 144,779 invitations from 47,571women.

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