Browsing by Author "Chimusa, E.R."
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Item Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection(nature research /scientific reports, 2021) Esoh, K.K.; Apinjoh, T.O.; Nyanjom, S.G.; Wonkam, A.; Chimusa, E.R.; Amenga‑Etego, L.; Amambua‑Ngwa, A.; Achidi, E.A.Inferences from genetic association studies rely largely on the defnition and description of the underlying populations that highlight their genetic similarities and diferences. The clustering of human populations into subgroups (population structure) can signifcantly confound disease associations. This study investigated the fne-scale genetic structure within Cameroon that may underlie disparities observed with Cameroonian ethnicities in malaria genome-wide association studies in sub-Saharan Africa. Genotype data of 1073 individuals from three regions and three ethnic groups in Cameroon were analyzed using measures of genetic proximity to ascertain fne-scale genetic structure. Model-based clustering revealed distinct ancestral proportions among the Bantu, Semi Bantu and Foulbe ethnic groups, while haplotype-based coancestry estimation revealed possible longstanding and ongoing sympatric diferentiation among individuals of the Foulbe ethnic group, and their Bantu and Semi-Bantu counterparts. A genome scan found strong selection signatures in the HLA gene region, confrming longstanding knowledge of natural selection on this genomic region in African populations following immense disease pressure. Signatures of selection were also observed in the HBB gene cluster, a genomic region known to be under strong balancing selection in sub-Saharan Africa due to its co-evolution with malaria. This study further supports the role of evolution in shaping genomes of Cameroonian populations and reveals fne-scale hierarchical structure among and within Cameroonian ethnicities that may impact genetic association studies in the country.Item Network‑driven analysis of human– Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets(Springer Nature, 2021) . Agamah, F.E; Damena, D.; Skelton, M.; Ghansah, A.; Mazandu, G.K.; Chimusa, E.R.Background: The emergence and spread of malaria drug resistance have resulted in the need to understand disease mechanisms and importantly identify essential targets and potential drug candidates. Malaria infection involves the complex interaction between the host and pathogen, thus, functional interactions between human and Plasmodium falciparum is essential to obtain a holistic view of the genetic architecture of malaria. Several functional interaction studies have extended the understanding of malaria disease and integrating such datasets would provide further insights towards understanding drug resistance and/or genetic resistance/susceptibility, disease pathogenesis, and drug discovery. Methods: This study curated and analysed data including pathogen and host selective genes, host and pathogen protein sequence data, protein–protein interaction datasets, and drug data from literature and databases to perform human-host and P. falciparum network-based analysis. An integrative computational framework is presented that was developed and found to be reasonably accurate based on various evaluations, applications, and experimental evidence of outputs produced, from data-driven analysis. Results: This approach revealed 8 hub protein targets essential for parasite and human host-directed malaria drug therapy. In a semantic similarity approach, 26 potential repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection that can be appropriated for malaria treatment. Further analysis of host–pathogen network shortest paths enabled the prediction of immunerelated biological processes and pathways subverted by P. falciparum to increase its within-host survival. Conclusions: Host–pathogen network analysis reveals potential drug targets and biological processes and pathways subverted by P. falciparum to enhance its within malaria host survival. The results presented have implications for drug discovery and will inform experimental studies.