Developing a multivariate prediction model of antibody features associated with protection of malaria-infected pregnant women from placental malaria

  1. Elizabeth H Aitken
  2. Timon Damelang
  3. Amaya Ortega-Pajares
  4. Agersew Alemu
  5. Wina Hasang
  6. Saber Dini
  7. Holger W Unger
  8. Maria Ome-Kaius
  9. Morten A Nielsen
  10. Ali Salanti
  11. Joe Smith
  12. Stephen Kent
  13. P Mark Hogarth
  14. Bruce D Wines
  15. Julie A Simpson
  16. Amy Chung
  17. Stephen J Rogerson  Is a corresponding author
  1. The University of Melbourne, Australia
  2. Royal Darwin Hospital, Australia
  3. Walter and Eliza Hall Institute of Medical Research, Australia
  4. University of Copenhagen, Denmark
  5. Seattle Children's Research Institute, United States
  6. Burnet Institute, Australia

Abstract

Background: Plasmodium falciparum causes placental malaria, which results in adverse outcomes for mother and child. P. falciparum infected erythrocytes that express the parasite protein VAR2CSA on their surface can bind to placental chondroitin sulfate-A. It has been hypothesized that naturally acquired antibodies towards VAR2CSA protect against placental infection, but it has proven difficult to identify robust antibody correlates of protection from disease. The objective of this study was to develop a prediction model using antibody features which could identify women protected from placental malaria.

Methods: We used a systems serology approach with elastic net-regularized logistic regression, Partial Least Squares Discriminant Analysis and a case control study design to identify naturally acquired antibody features mid pregnancy that were associated with protection from placental malaria at delivery in a cohort of 77 pregnant women from Madang, Papua New Guinea.

Results: The machine learning techniques selected six out of 169 measured antibody features towards VAR2CSA that could predict (with 86% accuracy) whether a woman would subsequently have active placental malaria infection at delivery. Selected features included previously described associations with inhibition of placental binding and/or opsonic phagocytosis of infected erythrocytes, and network analysis indicated that there are not one but multiple pathways to protection from placental malaria.

Conclusions: We have identified candidate antibody features which could accurately identify malaria-infected women as protected from placental infection. It is likely that there are multiple pathways to protection against placental malaria.

Funding: This study was supported by the National Health and Medical Research Council (No. APP1143946, GNT1145303, APP1092789, APP1140509 and APP1104975).

Data availability

All antibody feature data has been deposited in datadryad.

The following data sets were generated

Article and author information

Author details

  1. Elizabeth H Aitken

    Medicine (RMH), The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  2. Timon Damelang

    Microbiology and Immunology, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6150-4435
  3. Amaya Ortega-Pajares

    Medicine (RMH), The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  4. Agersew Alemu

    Medicine (RMH), The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  5. Wina Hasang

    Medicine (RMH), The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  6. Saber Dini

    Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  7. Holger W Unger

    Department of Obstetrics and Gynaecology, Royal Darwin Hospital, Darwin, Australia
    Competing interests
    The authors declare that no competing interests exist.
  8. Maria Ome-Kaius

    Population Health and Immunity Division, Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  9. Morten A Nielsen

    Centre for Medical Parasitology, Department of Microbiology and immunology, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2668-4992
  10. Ali Salanti

    Centre for Medical Parasitology, Department of Microbiology and immunology, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  11. Joe Smith

    Centre for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7915-6360
  12. Stephen Kent

    Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  13. P Mark Hogarth

    Burnet Institute, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  14. Bruce D Wines

    Burnet Institute, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  15. Julie A Simpson

    Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2660-2013
  16. Amy Chung

    Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  17. Stephen J Rogerson

    Medicine (RMH), The University of Melbourne, Melbourne, Australia
    For correspondence
    sroger@unimelb.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4287-1982

Funding

National Health and Medical Research Council (APP1143946)

  • Elizabeth H Aitken
  • Amy Chung
  • Stephen J Rogerson

National Health and Medical Research Council (GNT1145303)

  • P Mark Hogarth
  • Bruce D Wines

National Health and Medical Research Council (APP1092789)

  • Stephen J Rogerson

National Health and Medical Research Council (APP1140509)

  • Amy Chung

University of Melbourne

  • Amaya Ortega-Pajares

Australian Society for Parasitology

  • Elizabeth H Aitken

National Health and Medical Research Council (APP1104975)

  • Julie A Simpson

Bill and Melinda Gates Foundation (46099)

  • Stephen J Rogerson

Miller Foundation Australia

  • Amaya Ortega-Pajares

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

Ethics

Human subjects: Collection and use of plasma samples from women in PNG was approved by the PNG Institute of Medical Research Institutional Review Board, the PNG Medical Research Advisory Council and the Melbourne Health Human Research Ethics Committee. All participants provided informed written consent. The use of blood products from donors in Melbourne for isolation of primary cells, culture of parasites and leukocytes and for use as negative controls was approved by the Melbourne Health Human Research Ethics committee and the University of Melbourne Human Research Ethics committee.

Reviewing Editor

  1. Urszula Krzych, Walter Reed Army Institute of Research, United States

Publication history

  1. Received: December 15, 2020
  2. Accepted: June 16, 2021
  3. Accepted Manuscript published: June 29, 2021 (version 1)
  4. Version of Record published: June 29, 2021 (version 2)
  5. Version of Record updated: August 16, 2021 (version 3)

Copyright

© 2021, Aitken 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. Elizabeth H Aitken
  2. Timon Damelang
  3. Amaya Ortega-Pajares
  4. Agersew Alemu
  5. Wina Hasang
  6. Saber Dini
  7. Holger W Unger
  8. Maria Ome-Kaius
  9. Morten A Nielsen
  10. Ali Salanti
  11. Joe Smith
  12. Stephen Kent
  13. P Mark Hogarth
  14. Bruce D Wines
  15. Julie A Simpson
  16. Amy Chung
  17. Stephen J Rogerson
(2021)
Developing a multivariate prediction model of antibody features associated with protection of malaria-infected pregnant women from placental malaria
eLife 10:e65776.
https://doi.org/10.7554/eLife.65776

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