Tessema, S. | Search bioRxiv

bioRxiv2018

Protective immunity against severe malaria is associated with antibodies to a conserved repertoire of PfEMP1 variants

Extreme diversity of the major surface antigen and virulence determinant of the malaria parasite Plasmodium falciparum, Erythrocyte Membrane Protein-1 (PfEMP1), poses a major barrier to identifying targets of protective immunity. To overcome this problem, we developed a PfEMP1 protein microarray containing 456 DBL domains, which was used to characterize the immunome of a cohort of semi-immune children and to identify variants associated with protective immune responses. Children with high mean antibody levels to DBL group 2 had a 26-36% reduced risk of uncomplicated (clinical) malaria, however only 8 diverse DBL variants were weakly associated with protection from clinical malaria and had low predictive accuracy. On the other hand, children with high mean antibodies to DBL groups 1 and 2 (which are markers for pathogenic \"Type A\" PfEMP1) and elevated antibodies to 85 (18.6%) of individual DBL variants had a 70 -100% reduced risk of severe malaria. Of the top 20 predictive variants for severe disease protection, 17 were strongly associated with protection (86 - 100% reduction in risk of severe malaria) and had high predictive accuracy for severe disease risk. Many variants were conserved and had highly correlated antibody responses, including the three highest-ranking variants, which were linked to EPCR-binding CIDR domains. The results suggest that while immunity to uncomplicated malaria is characterised by antibodies to a diverse repertoire of PfEMP1, immunity to severe malaria requires antibodies to a limited subset of antigenically conserved variants. These findings provide new insights into antimalarial immunity and potential biomarkers for tracking disease risk.

microbiology↗

bioRxiv2018

Mapping malaria by combining parasite genomic and epidemiologic data

Recent global progress in scaling up malaria control interventions has revived the goal of complete elimination in many countries. Decreasing transmission intensity generally leads to increasingly patchy spatial patterns of malaria transmission, however, and control programs must accurately identify remaining foci in order to target interventions efficiently. In particular, mosquito control interventions like bed nets and insecticide spraying are best targeted to transmission hotspots, and the role of connectivity between different pockets of local transmission becomes increasingly important since humans are able to move parasites beyond the limits of mosquito dispersal and re-introduce parasites to previously malaria-free regions. Quantifying the connectivity between regions due to human travel, measuring malaria transmission intensity in different areas, and monitoring parasite spatial spread are therefore key issues for policy-makers because they underpin the feasibility of elimination and inform the path to its attainment. To this end, recent efforts have been made to develop new approaches to incorporating human mobility into spatial epidemiological models, for example using mobile phone data, and there has been a surge of interest in collecting spatially informative parasite samples to measure the genomic signatures of parasite connectivity. Due to their complicated life-cycles, Plasmodium parasites pose unique challenges to researchers in this respect and new methods that move beyond traditional phylogenetic and population genetic tools must be developed to harness genetic information effectively. Here, we discuss the spatial epidemiology of malaria in the context of transmission-reduction interventions, and the challenges and promising directions for the development of integrated mapping, modeling, and genomic approaches that leverage disparate data sets to measure both connectivity and transmission.

epidemiology↗