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Endothelial transcriptomic analysis identifies biomarkers of severe and cerebral malaria

Authors :
Cláudia Gomes
Rosauro Varo
Miquel Duran-Frigola
Antonio Sitoe
Rubão Bila
Sonia Machevo
Alfredo Mayor
Quique Bassat
Ana Rodriguez
Source :
JCI Insight, Vol 8, Iss 22 (2023)
Publication Year :
2023
Publisher :
American Society for Clinical investigation, 2023.

Abstract

Malaria can quickly progress from an uncomplicated infection into a life-threatening severe disease. However, the unspecificity of early symptoms often makes it difficult to identify patients at high risk of developing severe disease. Additionally, one of the most feared malaria complications — cerebral malaria — is challenging to diagnose, often resulting in treatment delays that can lead to adverse outcomes. To identify candidate biomarkers for the prognosis and/or diagnosis of severe and cerebral malaria, we have analyzed the transcriptomic response of human brain microvascular endothelial cells to erythrocytes infected with Plasmodium falciparum. Candidates were validated in plasma samples from a cohort of pediatric patients with malaria from Mozambique, resulting in the identification of several markers with capacity to distinguish uncomplicated from severe malaria, the most potent being the metallopeptidase ADAMTS18. Two other biomarkers, Angiopoietin-like-4 and Inhibin-βE were able to differentiate children with cerebral malaria within the severe malaria group, showing increased sensitivity after combination in a biomarker signature. The validation of the predicted candidate biomarkers in plasma of children with severe and cerebral malaria underscores the power of this transcriptomic approach and indicates that a specific endothelial response to P. falciparum–infected erythrocytes is linked to the pathophysiology of severe malaria.

Subjects

Subjects :
Infectious disease
Medicine

Details

Language :
English
ISSN :
23793708
Volume :
8
Issue :
22
Database :
Directory of Open Access Journals
Journal :
JCI Insight
Publication Type :
Academic Journal
Accession number :
edsdoj.860cefaf2ea545ce90cd8443e088c558
Document Type :
article
Full Text :
https://doi.org/10.1172/jci.insight.172845