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

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.The malaria parasite Plasmodium falciparum kills on the order of a million African children each year 1 , and this is a small fraction of the number of infected individuals in the population [1][2][3] . In communities where everyone is repeatedly infected with P. falciparum, host genetic factors account for ~25% of the risk of severe malaria, that is, life-threatening forms of the disease 3 . The strongest known determinant of risk, hemoglobin S (HbS), accounts for 2% of the total variation, implying that only a small fraction of genetic resistance factors have so far been discovered 3 . Identifying the genetic basis of protective immunity against severe malaria may provide important insights for vaccine development.Here we examine the possibility of approaching this problem by genome-wide association (GWA) analysis. There are many unsolved methodological questions about how to conduct an effective GWA study in Africa 4 . High levels of ethnic diversity may result in false-positive associations owing to population structure. Variations in haplotype structure between different ethnic groups may reduce power to detect GWA signals, particularly when data are amalgamated across multiple study sites. Low LD implies the need for denser genotyping arrays than are currently available: a crude estimate is that an African GWA study with 1.5 million SNPs would have approximately the same statistical power as a European study with Jallow et al.Page 2Nat Genet. Author manuscript; available in PMC 2010 September 21. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript 0.6 million SNPs5, but this is based on HapMap data from a single ethnic group and a larger number of SNPs may be needed to achieve adequate power across different ethnic groups.We carried out an initial GWA study in Gambian children that explores these methodological questions. Genotyping of ~500,000 SNPs was conducted on 1,060 cases of severe malaria and 1...

Population genetics of malaria resistance in humans

“…Other factors such as population structure and chance, as well as the experimental design or the phenotype(s) of malaria diagnosed in a given study, may impact the conclusions. Efforts to use genomics approaches and genome-wide association analysis have been initiated (Ayodo et al, 2007;Timmann et al, 2007;The Malaria Genomic Epidemiology Network, 2008;Jallow et al, 2009;Eid et al, 2010) and some new regions of potential malaria resistance have been identified.…”

Deciphering Complement Receptor Type 1 Interactions with Recognition Proteins of the Lectin Complement Pathway

“…The ethnic-specific distribution of two of these blood group variants, Sl1/2 (Lys/Glu 1590 at the CCP24-25 junction) and McC a/b (Arg/Gly 1601 in CCP25) has been proposed to result from selective pressures in malarial endemic regions of Africa. However, contradictory results have been obtained regarding their association with malarial severity in different African populations (52)(53)(54)(55). CR1 interacts with two P. falciparum proteins, the malarial adhesin PfEMP1 (14) and the PfRh4 invasion ligand (15), but the binding sites have been located to the C3b and C4b binding sites of CR1, respectively (20,21).…”

Genome-wide association studies of tuberculosis in Asians identify distinct at-risk locus for young tuberculosis

“…For several common infectious diseases, susceptibility loci with moderate to large effect sizes (at-risk odds ratios 41.5) were successfully identified by GWAS. For example, associations have been identified between HbS and malaria 5 and between CFH locus and infection by Neisseria meningitides. 6 Recently, a GWAS of two African TB populations identified a gene desert in 18q11.2 as a novel candidate locus for TB, but unlike GWASs in other common infectious diseases, GWASs of TB were not successful in identifying any genetic factors with moderate to large effect sizes.…”