Multiplexed quantitative proteomics provides mechanistic cues for malaria severity and complexity

Management of severe malaria remains a critical global challenge. In this study, using a multiplexed quantitative proteomics pipeline we systematically investigated the plasma proteome alterations in non-severe and severe malaria patients. We identified a few parasite proteins in severe malaria patients, which could be promising from a diagnostic perspective. Further, from host proteome analysis we observed substantial modulations in many crucial physiological pathways, including lipid metabolism, cytokine signaling, complement, and coagulation cascades in severe malaria. We propose that severe manifestations of malaria are possibly underpinned by modulations of the host physiology and defense machinery, which is evidently reflected in the plasma proteome alterations. Importantly, we identified multiple blood markers that can effectively define different complications of severe falciparum malaria, including cerebral syndromes and severe anemia. The ability of our identified blood markers to distinguish different severe complications of malaria may aid in developing new clinical tests for monitoring malaria severity. Kumar et al. use proteomes of patients with falciparum and vivax malaria and dengue fever, and identify differentially abundant proteins and their associated functions in the different severities and diseases. This study offers mechanistic pathways to malaria severity, and adopts a machine learning approach for predictive proteins for the malarial types and severities.