Purpose: Malaria is a life-threatening mosquito-borne disease caused by Plasmodium parasites, mainly in tropical and subtropical countries. Plasmodium falciparum (P. falciparum) is the most prevalent cause on the African continent and responsible for most malaria-related deaths globally. Important medical needs are biomarkers for disease severity or disease outcome. A potential source of easily accessible biomarkers are blood-borne small extracellular vesicles (sEVs).
Methods: We performed an EV Array to find proteins on plasma sEVs that are differentially expressed in malaria patients. Plasma samples from 21 healthy subjects and 15 malaria patients were analyzed. The EV array contained 40 antibodies to capture sEVs, which were then visualized with a cocktail of biotin-conjugated CD9, CD63, and CD81 antibodies.
Results: We detected significant differences in the protein decoration of sEVs between healthy subjects and malaria patients. We found CD106 to be the best discrimination marker based on receiver operating characteristic (ROC) analysis with an area under the curve of > 0.974. Additional ensemble feature selection revealed CD106, Osteopontin, CD81, major histocompatibility complex class II DR (HLA-DR), and heparin binding EGF like growth factor (HBEGF) together with thrombocytes to be a feature panel for discrimination between healthy and malaria. TNF-R-II correlated with HLA-A/B/C as well as CD9 with CD81, whereas Osteopontin negatively correlated with CD81 and CD9. Pathway analysis linked the herein identified proteins to IFN-γ signaling.
Conclusion: sEV-associated proteins can discriminate between healthy individuals and malaria patients and are candidates for future predictive biomarkers.
Trial registration: The trial was registered in the Deutsches Register Klinischer Studien (DRKS-ID: DRKS00012518).
Keywords: Biomarker; Ensemble feature selection; Extracellular vesicles; IFN-γ; Malaria.
© 2023. The Author(s).