The impact of malaria-protective red blood cell polymorphisms on parasite biomass in children with severe Plasmodium falciparum malaria

Severe falciparum malaria is a major cause of preventable child mortality in sub-Saharan Africa. Plasma concentrations of P. falciparum Histidine-Rich Protein 2 (PfHRP2) have diagnostic and prognostic value in severe malaria. We investigate the potential use of plasma PfHRP2 and the sequestration index (the ratio of PfHRP2 to parasite density) as quantitative traits for case-only genetic association studies of severe malaria. Data from 2198 Kenyan children diagnosed with severe malaria, genotyped for 14 major candidate genes, show that polymorphisms in four major red cell genes that lead to hemoglobin S, O blood group, α-thalassemia, and the Dantu blood group, are associated with substantially lower admission plasma PfHRP2 concentrations, consistent with protective effects against extensive parasitized erythrocyte sequestration. In contrast the known protective ATP2B4 polymorphism is associated with higher plasma PfHRP2 concentrations, lower parasite densities and a higher sequestration index. We provide testable hypotheses for the mechanism of protection of ATP2B4.

Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision

Severe falciparum malaria has substantially affected human evolution. Genetic association studies of patients with clinically defined severe malaria and matched population controls have helped characterise human genetic susceptibility to severe malaria, but phenotypic imprecision compromises discovered associations. In areas of high malaria transmission, the diagnosis of severe malaria in young children and, in particular, the distinction from bacterial sepsis are imprecise. We developed a probabilistic diagnostic model of severe malaria using platelet and white count data. Under this model, we re-analysed clinical and genetic data from 2220 Kenyan children with clinically defined severe malaria and 3940 population controls, adjusting for phenotype mis-labelling. Our model, validated by the distribution of sickle trait, estimated that approximately one-third of cases did not have severe malaria. We propose a data-tilting approach for case-control studies with phenotype mis-labelling and show that this reduces false discovery rates and improves statistical power in genome-wide association studies.