BMC Medical GenomicsGenomicsPeer-reviewed journal article
Genome-Wide Association Studies of malaria susceptibility and resistance: progress, pitfalls and prospects
Delesa DamenaiD, Denis AwanyiD, Lemu GolassaiD, Emile Rugamika ChimusaiD
Abstract
P. falciparum malaria is still among the leading causes of child mortality in sub-Saharan Africa; killing hundreds of thousands of children each year. Malaria has been recognized as one of the prominent evolutionary selective forces of human genome that led to the emergence of multiple host protective polymorphisms associated with minimizing the risk of developing severe malaria in endemic areas. A comprehensive understanding of the genetic bases of malaria resistance can shed light to the molecular mechanisms of host-parasite interactions that can potentially pave ways to the development of new therapeutics and vaccines. Genome-wide association studies (GWASs) have recently been implemented in malaria endemic areas and identified a number of novel association genetic variants. Despite this success, only few variants did replicate across the studies and the underlying biology is yet to be understood for the majority of the novel variants. Besides, there are several open questions around heritability, polygenic effects, epistatic interactions, genetic correlations and associated molecular pathways among others. In this review, we first assess the progress and pitfalls of malaria susceptibility GWASs. We then, provide an overview of the current progress in post-GWAS approaches and discuss how these approaches can potentially be implemented in malaria susceptibility GWASs to extract further functional information. We conclude by highlighting the importance of multi-step and multidimensional integrative studies for unravelling the genetic basis of malaria susceptibility and resistance at systems biology level.
- organism: human
- assay: GWAS summary statistics
- research focus: benchmarking
- research focus: GWAS / association mapping
- research focus: fine-mapping
- research focus: eQTL / molecular QTL mapping
- approach: statistical model
- Citations
- 35
- FWCI
- 0.98
- Field percentile
- top 29%
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