Uyoga, S. | Search bioRxiv

bioRxiv2022

Non-O ABO blood group genotypes differ in their associations with Plasmodium falciparum rosetting and severe malaria

Blood group O is associated with protection against severe malaria and reduced size and stability of P. falciparum-host red blood cell (RBC) rosettes compared to non-O blood groups. Whether the non-O blood groups encoded by the specific ABO genotypes AO, BO, AA, BB and AB differ in their associations with severe malaria and rosetting is unknown. The A and B antigens are host RBC receptors for rosetting, hence we hypothesized that the higher levels of A and/or B antigen on RBCs from AA, BB and AB genotypes compared to AO/BO genotypes could lead to larger rosettes, increased microvascular obstruction and higher risk of malaria pathology. We used a case-control study of Kenyan children and in vitro adhesion assays to test the hypothesis that "double dose" non-O genotypes (AA, BB, AB) are associated with increased risk of severe malaria and larger rosettes than "single dose" heterozygotes (AO, BO). In the case-control study, compared to OO, the double dose genotypes consistently had higher odds ratios (OR) for severe malaria than single dose genotypes, with AB (OR 1.93) and AO (OR 1.27) showing most marked difference (P=0.02, Wald test). In vitro experiments with blood group A-preferring P. falciparum parasites showed that significantly larger rosettes were formed with AA and AB host RBCs compared to OO, whereas AO genotype rosettes were indistinguishable from OO. Overall, the data show that ABO genotype influences P. falciparum rosetting and support the hypothesis that double dose non-O genotypes confer a greater risk of severe malaria than AO/BO heterozygosity.

genetics↗

bioRxiv2021

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, is 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 2,220 Kenyan children with clinically defined severe malaria and 3,940 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.

genetics↗