Common virulence gene expression in adult first-time infected malaria patients and severe cases

J Stephan Wichers1,2,3, Gerry Tonkin-Hill4, Thorsten Thye5

  • 1Molecular Biology and Immunology, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.

Elife
|April 28, 2021
PubMed

Insights

Severe malaria is linked to Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) binding the endothelial protein C receptor (EPCR). Non-severe cases involve CD36-binding PfEMP1, particularly in malaria-naive individuals.

Area of Science:

  • Malariology
  • Immunology
  • Genomics

Background:

  • Sequestration of Plasmodium falciparum-infected erythrocytes via PfEMP1 proteins drives malaria pathogenesis.
  • PfEMP1 proteins exhibit diverse variants, influencing parasite binding to human endothelial receptors.

Purpose of the Study:

  • To investigate the association between PfEMP1 variants and malaria severity in adult travelers.
  • To correlate specific PfEMP1 binding phenotypes with clinical outcomes in Plasmodium falciparum infections.

Main Methods:

  • RNA-sequencing (RNA-seq) analysis of Plasmodium falciparum isolates from 32 infected travelers.
  • De novo assembly of PfEMP1-encoding var gene transcripts and analysis of var-expressed sequence tags.
  • Categorization of patients based on malaria exposure (naive vs. pre-exposed) and disease severity (severe vs. non-severe).

Main Results:

  • Severe malaria cases were associated with PfEMP1 variants binding the endothelial protein C receptor (EPCR).
  • Non-severe malaria outcomes correlated with CD36-binding PfEMP1 variants.
  • First-time infected adults were more prone to severe symptoms and longer infection duration.

Conclusions:

  • Parasites expressing pathogenic PfEMP1 variants, particularly EPCR-binding types, are more prevalent in malaria-naive patients.
  • Adverse inflammatory responses during initial infections may favor the proliferation of EPCR-binding Plasmodium falciparum strains.
  • Understanding PfEMP1-receptor interactions is crucial for predicting and managing malaria severity.