The clinical presentation of severe Plasmodium falciparum malaria differs between children and adults, but the mechanistic basis for this remains unclear. Contributing factors to disease severity include total parasite biomass and the diverse cytoadhesive properties mediated by the polymorphic var gene parasite ligand family displayed on infected erythrocytes. To explore these factors, we performed a multicohort analysis of the contribution of var expression and parasite biomass to severe malaria in two previously published pediatric cohorts in Tanzania and Malawi and an adult cohort in India. Machine learning analysis revealed independent and complementary roles for var adhesion types and parasite biomass in adult and pediatric severe malaria and showed that similar var profiles, including upregulation of group A and DC8 var, predict severe malaria in adults and children. Among adults, patients with multiorgan complications presented infections with significantly higher parasite biomass without significant differences in var adhesion types. Conversely, pediatric patients with specific complications showed distinct var signatures. Cerebral malaria patients showed broadly increased expression of var genes, in particular group A and DC8 var, while children with severe malaria anemia were classified based on high transcription of DC8 var only. This study represents the first large multisite meta-analysis of var expression, and it demonstrates the presence of common var profiles in severe malaria patients of different ages across distant geographical sites, as well as syndrome-specific disease signatures. The complex associations between parasite biomass, var adhesion type, and clinical presentation revealed here represent the most comprehensive picture so far of the relationship between cytoadhesion, parasite load, and clinical syndrome.IMPORTANCE P. falciparum malaria can cause multiple disease complications that differ by patient age. Previous studies have attempted to address the roles of parasite adhesion and biomass in disease severity; however, these studies have been limited to single geographical sites, and there is limited understanding of how parasite adhesion and biomass interact to influence disease manifestations. In this meta-analysis, we compared parasite disease determinants in African children and Indian adults. This study demonstrates that parasite biomass and specific subsets of var genes are independently associated with detrimental outcomes in both childhood and adult malaria. We also explored how parasite var adhesion types and biomass play different roles in the development of specific severe malaria pathologies, including childhood cerebral malaria and multiorgan complications in adults. This work represents the largest study to date of the role of both var adhesion types and biomass in severe malaria.
Keywords: PfEMP1; Plasmodium falciparum; cerebral malaria; machine learning; malaria; severe malaria; var gene.
Copyright © 2019 Duffy et al.