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Determinants of brain swelling in pediatric and adult cerebral malaria
Praveen K. Sahu, … , Maria Bernabeu, Samuel C. Wassmer
Praveen K. Sahu, … , Maria Bernabeu, Samuel C. Wassmer
Published September 22, 2021
Citation Information: JCI Insight. 2021;6(18):e145823. https://doi.org/10.1172/jci.insight.145823.
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Research Article Infectious disease Microbiology

Determinants of brain swelling in pediatric and adult cerebral malaria

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Abstract

Cerebral malaria (CM) affects children and adults, but brain swelling is more severe in children. To investigate features associated with brain swelling in malaria, we performed blood profiling and brain MRI in a cohort of pediatric and adult patients with CM in Rourkela, India, and compared them with an African pediatric CM cohort in Malawi. We determined that higher plasma Plasmodium falciparum histidine rich protein 2 (PfHRP2) levels and elevated var transcripts that encode for binding to endothelial protein C receptor (EPCR) were linked to CM at both sites. Machine learning models trained on the African pediatric cohort could classify brain swelling in Indian children CM cases but had weaker performance for adult classification, due to overall lower parasite var transcript levels in this age group and more severe thrombocytopenia in Rourkela adults. Subgrouping of patients with CM revealed higher parasite biomass linked to severe thrombocytopenia and higher Group A–EPCR var transcripts in mild thrombocytopenia. Overall, these findings provide evidence that higher parasite biomass and a subset of Group A–EPCR binding variants are common features in children and adult CM cases, despite age differences in brain swelling.

Authors

Praveen K. Sahu, Fergal J. Duffy, Selasi Dankwa, Maria Vishnyakova, Megharay Majhi, Lukas Pirpamer, Vladimir Vigdorovich, Jabamani Bage, Sameer Maharana, Wilson Mandala, Stephen J. Rogerson, Karl B. Seydel, Terrie E. Taylor, Kami Kim, D. Noah Sather, Akshaya Mohanty, Rashmi R. Mohanty, Anita Mohanty, Rajyabardhan Pattnaik, John D. Aitchison, Angelika Hoffmann, Sanjib Mohanty, Joseph D. Smith, Maria Bernabeu, Samuel C. Wassmer

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Figure 7

Machine learning models and individual contribution of parasite biomass and Group A–EPCR variants in patients with CM with mild or severe thrombocytopenia in Malawi and India.

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Machine learning models and individual contribution of parasite biomass ...
(A) Bar graphs representing the importance of parasite factors in random forest models that classify patients with CM with different degrees of thrombocytopenia (mild > 50,000 platelets/μL; severe < 50,000 platelets/μL). Left: Patients with CM with mild thrombocytopenia versus UM. Middle: CM with severe thrombocytopenia versus UM. Positive MDCA (left and middle graphs) indicate greater presence in CM than in patients with UM. Asterisks show significant difference between groups measured by mProbes algorithm ([FWER] ≤ 0.2). Right: Patients with CM with mild thrombocytopenia versus CM with severe thrombocytopenia. Positive MDCA indicates higher association in CM with mild thrombocytopenia, and negative MDCA indicates higher association in CM with severe thrombocytopenia. Features include: plasma PfHRP2 concentration (PfHRP2), and var domain transcriptional units. (B) ROC curves showing the predictive performance of each model. Performance is measured by AUC, indicated in the legend with 95% CI in parentheses. (C) Transcripts levels of Group A–EPCR (DBLα1.7 [DC13], CIDRα1.5 and CIDRα1.6) in patients with CM with mild thrombocytopenia (CM>P; peripheral platelets > 50,000/μL; Malawi n = 33, India n = 7), CM with severe thrombocytopenia (CM<P; peripheral platelets < 50,000/μL; Malawi n = 27, India n = 20), and combined UM from India and Malawi (Malawi n = 38, India n = 8). Horizontal lines represent median, and boxes represent interquartile range. Significance was determined by FDR-adjusted Wilcoxon P values.

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