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

James A Watson,Gideon Nyutu,Kathryn Maitland,Philip Bejon,Hugh Kingston,Neema Mturi,Norbert Peshu,Sophie Uyoga,Benjamin Tsofa,Caroline Ngetsa,Shebe Mohammed,Alexander Macharia,Nicholas P J Day ,Carolyne Ndila ,Kirk A Rockett ,Arjen M Dondorp ,Stije J Leopold ,Thomas N Williams ,Chris Holmes ,Elizabeth C George ,Nicholas J White

doi:10.7554/elife.69698

Abstract

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.

Highlights

Severe malaria caused by the parasite Plasmodium falciparum kills nearly half a million children each year, mostly in sub-Saharan Africa (World Health Organization, 2020)
To illustrate this important point, in a cohort of 566 severely ill Ugandan children enrolled in the Fluid Expansion as Supportive Therapy (FEAST) trial (Maitland et al, 2011), a trial including all severe illness not restricted to severe malaria, low platelet counts were highly
Diagnostic specificity can be improved by visualisation of the obstructed microcirculation in vivo or from parasite biomass indicators, but these are still largely research procedures and have not been widely adopted or measured at scale for genetic association studies

Summary

Introduction

Severe malaria caused by the parasite Plasmodium falciparum kills nearly half a million children each year, mostly in sub-Saharan Africa (World Health Organization, 2020). Epidemiology and Global Health Genetics and Genomics eLife digest In areas of sub-Saharan Africa where malaria is common, most people are frequently exposed to the bites of mosquitoes carrying malaria parasites, so they often have malaria parasites in their blood. Young children, who have not yet built up strong immunity against malaria, often fall ill with severe malaria, a life-threatening disease. It is unclear why some children develop severe malaria and die, while other children with high numbers of parasites in their blood do not develop any apparent symptoms

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