Association Analysis of Additive Effects and Epistasis Between Human Candidate Malaria Protective Genes

Ndia, Carolyne Mukami (2015). Association Analysis of Additive Effects and Epistasis Between Human Candidate Malaria Protective Genes. PhD thesis The Open University.

DOI: https://doi.org/10.21954/ou.ro.0000ef66

Abstract

Malaria is a major cause of childhood death in Africa and host genetic factors play a key role in determining survival from this disease. Although many candidate loci have been identified, there have been difficulties in confirming the significance of some of these loci. To some extent this might be explained by the added complexity of epistasis, or gene-gene interactions. Through this thesis I aimed: (1) to re-appraise a range of candidate malaria-association genes using a large-scale case-control study of severe malaria (SM) in Kilifi, Kenya; (2) to compare different approaches to detecting epistatic interactions; (3) to look for evidence of epistasis between candidate genes in my data set; (4) to examine the haplotype structure and linkage disequilibrium (LD) patterns for two such implicated variants (HbS and α+thalassaemia) and their gene regions, that coexist in the Kilifi population, and (5) to use these exemplars as a starting point for investigating the process of detecting epistasis in SM in a genome-wide association study (GWAS). Out of 71 candidate genes investigated, I observed that polymorphisms affecting various aspects of red blood cells (including HBB, HBA, G6PD, FREM3, INPP4B, ATP2B4 and ABO) were among those associated with the strongest signals of differential susceptibility to SM. Because of their prominence in malaria, HbS and α+thalassaemia were used to illustrate interaction analysis at the GWAS level. This included looking at the structure of the genomic regions surrounding the genes. As expected, a single haplotype of approximately 200kb was seen surrounding HbS, which then diverged into 2 major haplotypes spanning a further 1Mb either side, an observation that was largely explained by ethnicity. In contrast, no marked LD/haplotype structure was observed in the genomic region surrounding the α+thalassaemia deletion, suggesting that this is a very old polymorphism. Through this study, I confirmed the negative epistasis seen between HbS and α+thalassaemia using a study design (case-control) that was different to that used previously (cohort), although this was not among the most significant of the interactions I detected. I searched for pairwise interactions between these two polymorphisms at a genome wide level using heterozygous and additive models for HbS and α+thalassaemia respectively. For each scan a single region reaching a significance level of <10-7 was found (STX18 for HbS and MYEOV for α+thalassaemia), plus several other novel signals were identified in the 10-6 to 10-7 significance region. Further work will be required to validate these signals and the challenge will be to try and understand their biological relevance. This is now becoming possible with datasets in many diseases, including malaria, being released into the public domain. But, as this Kenyan study has shown, having large group sizes, high quality clinical and genetic data, it is possible to begin to explore genetic interactions in a disease setting.

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