Candidate malaria susceptibility/protective SNPs in hospital and population-based studies: the effect of sub-structuring

Abstract

BackgroundPopulations of East Africa including Sudan, exhibit some of the highest indices of genetic diversity in the continent and worldwide. The current study aims to address the possible impact of population structure and population stratification on the outcome of case-control association-analysis of malaria candidate-genes in different Sudanese populations, where the pronounced genetic heterogeneity becomes a source of concern for the potential effect on the studies outcome.MethodsA total of 72 SNPs were genotyped using the Sequenom® iPLEX Gold assay in 449 DNA samples that included; cases and controls from two village populations, malaria patients and out-patients from the area of Sinnar and additional controls consisting of healthy Nilo-Saharan speaking individuals. The population substructure was estimated using the Structure 2.2 programme.Results & DiscussionThe Hardy-Weinberg Equilibrium values were generally within expectation in Hausa and Massalit. However, in the Sinnar area there was a notable excess of homozygosity, which was attributed to the Whalund effect arising from population amalgamation within the sample. The programme STRUCTURE revealed a division of both Hausa and Massalit into two substructures with the partition in Hausa more pronounced than in Massalit; In Sinnar there was no defined substructure. More than 25 of the 72 SNPs assayed were informative in all areas. Some important SNPs were not differentially distributed between malaria cases and controls, including SNPs in CD36 and NOS2. A number of SNPs showed significant p-values for differences in distribution of genotypes between cases and controls including: rs1805015 (in IL4R1) (P = 0.001), rs17047661 (in CR1) (P = 0.02) and rs1800750 (TNF-376)(P = 0.01) in the hospital samples; rs1050828 (G6PD+202) (P = 0.02) and rs1800896 (IL10-1082) (P = 0.04) in Massalit and rs2243250 (IL4-589) (P = 0.04) in Hausa.ConclusionsThe difference in population structure partly accounts for some of these significant associations, and the strength of association proved to be sensitive to all levels of sub-structuring whether in the hospital or population-based study.

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.…”

Host candidate gene polymorphisms and associated clearance ofP. falciparumamodiaquine and fansidar resistance mutants in children less than 5 years in Cameroon

“…24 Our analysis of infecting parasite genotypes and treatment outcome did not show any strong and independent association between known parasite resistance markers and treatment response. The host immune response represents a key factor that may interfere in the relationship between levels of drug resistant markers and observed treatment failure 35,36 in in vivo drug studies. In individuals exposed to malaria for their first time, infection with the malaria parasite does not always lead to severe disease.…”

“…It should be noted that the sample size was determined to test for clinical efficacy and safety and not for association analysis, which would have been much larger. In addition, the contribution of minor alleles in defining treatment outcomes would be possible only with very large samples size and population substructuring as was observed in a hospital-based and population-based study 35 evaluating candidate malaria susceptibility/resistant genes. Nevertheless, these findings flag the involvement of IL-22, IL-4R1, IL-10, IL-17, CD36, and TNF-SM2 in protective responses to malaria infections and treatment in Cameroonian children.…”

Human Genetic Contribution to the Outcome of Infection with Malaria Parasites

“…The past decade has seen growing evidence of ethnic differences in susceptibility to malaria and of the diverse genetic adaptations to malaria that have arisen in different populations. The fact that different malaria-resistance alleles have arisen in different places suggests that a great deal of selection by malaria has happened relatively recently in human history and certainly since human migration out of Africa (Eid et al, 2010). Such population differences in susceptibility to malaria are becoming more amenable to study since the development of high through-put genetic technology, thereby allowing us to genetically dissect the outcome of infection.…”