A mechanistic model for long-term immunological outcomes in South African HIV-infected children and adults receiving ART

  1. Eva Liliane Ujeneza  Is a corresponding author
  2. Wilfred Ndifon
  3. Shobna Shawry
  4. Geoffrey Fatti
  5. Julien Riou
  6. Mary-Ann Davies
  7. Martin Nieuwoudt
  8. IeDEA-Southern Africa collaboration
  1. Stellenbosch University, South Africa
  2. African Institute for Mathematical Sciences Next Einstein Initiative, Rwanda
  3. University of the Witwatersrand, South Africa
  4. Kheth'Impilo AIDS Free Living, Division of Epidemiology and Biostatistics, South Africa
  5. University of Bern, Switzerland
  6. University of Cape Town, South Africa

Abstract

Long-term effects of the growing population of HIV-treated people in Southern Africa on individuals and the public health sector at large are not yet understood. This study proposes a novel 'ratio' model that relates CD4+ T-cell counts of HIV-infected individuals to the CD4+ count reference values from healthy populations. We use mixed-effects regression to fit the model to data from 1,616 children (median age 4.3 years at ART initiation) and 14,542 adults (median age 36 years at ART initiation). We found that the scaled carrying capacity, maximum CD4+ count relative to an HIV-negative individual of similar age, and baseline scaled CD4+ counts were closer to healthy values in children than in adults. Post-ART initiation, CD4+ growth rate was inversely correlated with baseline CD4+ T-cell counts, and consequently higher in adults than children. Our results highlight the impacts of age on dynamics of the immune system of healthy and HIV-infected individuals.

Data availability

Data used is from the International epidemiologic Databases to Evaluate AIDS Southern Africa collaboration. They maintain a database of routinely collected data from various clinics , mostly located in South Africa. We recommend that interested readers contact Dr. Morna Cornell, Project Manager IeDEA-SA in Cape Town (morna.cornell@uct.ac.za) to establish a data-sharing agreement. A research proposal highlighting how the data will be used is required.Source data for Figures / Figure supplements are provided and the Source code is available via GitHub.

Article and author information

Author details

  1. Eva Liliane Ujeneza

    DST/NRF South African Center for Epidemiological Modelling and Analysis (SACEMA), Mathematics, Stellenbosch University, Stellenbosch, South Africa
    For correspondence
    ujeneva@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5760-4847
  2. Wilfred Ndifon

    Research, African Institute for Mathematical Sciences Next Einstein Initiative, Kigali, Rwanda
    Competing interests
    The authors declare that no competing interests exist.
  3. Shobna Shawry

    Wits Reproductive Health and HIV Institute, University of the Witwatersrand, Johannesburg, South Africa
    Competing interests
    The authors declare that no competing interests exist.
  4. Geoffrey Fatti

    Research, Kheth'Impilo AIDS Free Living, Division of Epidemiology and Biostatistics, Cape Town, South Africa
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6467-662X
  5. Julien Riou

    Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  6. Mary-Ann Davies

    Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine and Family Medecine, University of Cape Town, Cape Town, South Africa
    Competing interests
    The authors declare that no competing interests exist.
  7. Martin Nieuwoudt

    DST/NRF South African Center for Epidemiological Modelling and Analysis, Institute for Biomedical Engineering (IBE), Stellenbosch University, Stellenbosch, South Africa
    Competing interests
    The authors declare that no competing interests exist.
  8. IeDEA-Southern Africa collaboration

Funding

Schlumberger Foundation

  • Eva Liliane Ujeneza

South African Department of Science and Technology and the National Research Foundation's Center of Excellence for Modelling and Analysis of Epidemiological Data

  • Eva Liliane Ujeneza

National Institute Of Allergy And Infectious Diseases of the National Institutes of Health under Award Number (U01AI069924)

  • Mary-Ann Davies

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

Ethics

Human subjects: This study was approved as part of the IeDEA Southern African collaboration's protocol, by the Human Research Ethics Committee of the University of Cape Town, with a reference number N1810119 RECIP UCT 084/2006. Informed consent was obtained from all participants by the clinics collecting the data according to IeDEA protocols.

Reviewing Editor

  1. Miles P Davenport, University of New South Wales, Australia

Publication history

  1. Received: September 27, 2018
  2. Accepted: January 13, 2021
  3. Accepted Manuscript published: January 14, 2021 (version 1)
  4. Version of Record published: February 3, 2021 (version 2)

Copyright

© 2021, Ujeneza 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.

Metrics

  • 617
    Page views
  • 107
    Downloads
  • 1
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Eva Liliane Ujeneza
  2. Wilfred Ndifon
  3. Shobna Shawry
  4. Geoffrey Fatti
  5. Julien Riou
  6. Mary-Ann Davies
  7. Martin Nieuwoudt
  8. IeDEA-Southern Africa collaboration
(2021)
A mechanistic model for long-term immunological outcomes in South African HIV-infected children and adults receiving ART
eLife 10:e42390.
https://doi.org/10.7554/eLife.42390

Further reading

    1. Microbiology and Infectious Disease
    Saba Naz, Kumar Paritosh ... Vinay Kumar Nandicoori
    Research Article Updated

    The emergence of drug resistance in Mycobacterium tuberculosis (Mtb) is alarming and demands in-depth knowledge for timely diagnosis. We performed genome-wide association analysis using 2237 clinical strains of Mtb to identify novel genetic factors that evoke drug resistance. In addition to the known direct targets, we identified for the first time, a strong association between mutations in DNA repair genes and the multidrug-resistant phenotype. To evaluate the impact of variants identified in the clinical samples in the evolution of drug resistance, we utilized knockouts and complemented strains in Mycobacterium smegmatis and Mtb. Results show that variant mutations compromised the functions of MutY and UvrB. MutY variant showed enhanced survival compared with wild-type (Rv) when the Mtb strains were subjected to multiple rounds of ex vivo antibiotic stress. In an in vivo guinea pig infection model, the MutY variant outcompeted the wild-type strain. We show that novel variant mutations in the DNA repair genes collectively compromise their functions and contribute to better survival under antibiotic/host stress conditions.

    1. Immunology and Inflammation
    2. Microbiology and Infectious Disease
    Justin L Roncaioli, Janet Peace Babirye ... Russell E Vance
    Research Advance Updated

    Bacteria of the genus Shigella cause shigellosis, a severe gastrointestinal disease driven by bacterial colonization of colonic intestinal epithelial cells. Vertebrates have evolved programmed cell death pathways that sense invasive enteric pathogens and eliminate their intracellular niche. Previously we reported that genetic removal of one such pathway, the NAIP–NLRC4 inflammasome, is sufficient to convert mice from resistant to susceptible to oral Shigella flexneri challenge (Mitchell et al., 2020). Here, we investigate the protective role of additional cell death pathways during oral mouse Shigella infection. We find that the Caspase-11 inflammasome, which senses Shigella LPS, restricts Shigella colonization of the intestinal epithelium in the absence of NAIP–NLRC4. However, this protection is limited when Shigella expresses OspC3, an effector that antagonizes Caspase-11 activity. TNFα, a cytokine that activates Caspase-8-dependent apoptosis, also provides potent protection from Shigella colonization of the intestinal epithelium when mice lack both NAIP–NLRC4 and Caspase-11. The combined genetic removal of Caspases-1, -11, and -8 renders mice hyper-susceptible to oral Shigella infection. Our findings uncover a layered hierarchy of cell death pathways that limit the ability of an invasive gastrointestinal pathogen to cause disease.