Genome-wide and fine-resolution association analysis of malaria in West Africa

Wellcome Trust Case Control Consortium, Muminatou Jallow, Yik Ying Teo, Kerrin S Small, Kirk A Rockett, Panos Deloukas, Taane G Clark, Katja Kivinen, Kalifa A Bojang, David J Conway, Margaret Pinder, Giorgio Sirugo, Fatou Sisay-Joof, Stanley Usen, Sarah Auburn, Suzannah J Bumpstead, Susana Campino, Alison Coffey, Andrew Dunham, Andrew E FryAngela Green, Rhian Gwilliam, Sarah E Hunt, Michael Inouye, Anna E Jeffreys, Alieu Mendy, Aarno Palotie, Simon Potter, Jiannis Ragoussis, Jane Rogers, Kate Rowlands, Elilan Somaskantharajah, Pamela Whittaker, Claire Widden, Peter Donnelly, Bryan Howie, Jonathan Marchini, Andrew Morris, Miguel SanJoaquin, Eric Akum Achidi, Tsiri Agbenyega, Angela Allen, Olukemi Amodu, Patrick Corran, Abdoulaye Djimde, Amagana Dolo, Ogobara K Doumbo, Chris Drakeley, Sarah Dunstan, Jennifer Evans, Jeremy Farrar

Research output: Contribution to journalArticlepeer-review

Abstract

We report a genome-wide association (GWA) study of severe malaria in The Gambia. The initial GWA scan included 2,500 children genotyped on the Affymetrix 500K GeneChip, and a replication study included 3,400 children. We used this to examine the performance of GWA methods in Africa. We found considerable population stratification, and also that signals of association at known malaria resistance loci were greatly attenuated owing to weak linkage disequilibrium (LD). To investigate possible solutions to the problem of low LD, we focused on the HbS locus, sequencing this region of the genome in 62 Gambian individuals and then using these data to conduct multipoint imputation in the GWA samples. This increased the signal of association, from P = 4 × 10(-7) to P = 4 × 10(-14), with the peak of the signal located precisely at the HbS causal variant. Our findings provide proof of principle that fine-resolution multipoint imputation, based on population-specific sequencing data, can substantially boost authentic GWA signals and enable fine mapping of causal variants in African populations.
Original languageEnglish
Pages (from-to)657-65
Number of pages9
JournalNature Genetics
Volume41
Issue number6
DOIs
Publication statusPublished - 2009

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