Human host and malaria parasite genome variations to susceptibility to malaria - Hordofa, Hundaol (Department of Clinical Laboratory Sciences, 2024)
Background: Inter-ethnic differences in response to medication can be explained through population structure as observed from genetic variants affecting drug metabolism. Antimalarial drugs are used in populations carrying different profiles of genetic variability. However, there is limited information on the distribution of genetic variants of pharmacogenomics importance in African populations. Aims: We set out to determine whether there are differences in the pharmacogenetic profiles when comparing populations residing in malaria endemic and non-endemic areas. Methodology: Genome-wide genotype datasets (n=13, 447) from four malaria endemic African populations, including Mali, Kenya, Gambia, and Malawi, which were part of the MalariaGEN consortium, were accessed. As comparator, reference datasets of global populations comprising of 20 ethnic groups (n~5,000) from African Genome Variation Project (AGVP) and 1000 Genome consortium project were accessed, considering their malaria epidemiology. Pharmacogenes that are verified from databases such as PharmVar and PharmGKB, and nomenclature sites for uridine 5'-diphospho-glucuronosyltransferases (UGT), solute carrier (SLC) transporters, ATP-binding cassette (ABC) transporters, thiopurine Smethyl transferase (TPMT), and N-acetyltransferases (NAT) were used. Pharmacogenes reported to affect antimalarial drugs were noted and their distribution analysed. Single nucleotide polymorphisms (SNPs) that map to pharmacogenes were retrieved from dbSNP databases and used in the comparison of the populations from malaria endemic and nonendemic regions, through population structure evaluation using pharmacogenes variants. As part of confirmation, genotyping for CYP2C8 SNPs was carried out in native South African population groups, which we have access to our laboratory. CYP2C8 is particularly interesting because of its central involvement in the metabolism of some of the major antimalarial drugs. Results: There were quantitative and qualitative differences in the distribution of pharmacogenes variants when comparing populations from malaria endemic regions to those from non-endemic regions. For instance, the analysis of the minor allele frequency (MAF) proportion of all pharmacogenes variants obtained from the databases revealed that a high proportion of common variants (MAF > 0.05) of pharmacogenes were higher in the four African population from malaria endemic areas (MAF proportion > 50%) compared with world populations from malaria non-endemic areas (MAF proportion < 50%). There were a disproportionately higher number of variants in cytochrome P450 enzymes such as CYP2A13 and CYP2F1 in the malaria endemic populations (> 80%) compared to non-endemic populations (< 65%). Further analysis based on antimalarial specific pharmacogenes variants showed that UGT1A9 had the highest proportion of variants (> 80%) in the malaria endemic populations. The ABC drug transporters such as ABCC4, ABCC1 and ABCC2 were found to have a higher proportion of pathogenic SNPs in populations of the four malaria endemic areas (> 50%) compared with those from non-endemic areas (< 30%). Principal component analysis (PCA) based on pharmacogenes variants also showed clear differentiation into different population. Moreover, four CYP2C8 variants (rs11572103T>A (*2), rs11572101A>G, rs11572100T>C and rs1926705C>T), characterized in South Africans, were found to have III statistically significant difference (p-value < 0.05) in allele frequency when compared with global populations. Conclusions: The findings from this study revealed the profiles of pharmacogenes variants in populations from malaria endemic and non-endemic geographical regions. The variants in CYP2A13, CYP2F1, and UGT1A9 were found in higher proportions in populations from malaria endemic areas compared to non-malaria endemic areas. This suggests that pharmacogenetic testing for patients based on antimalarial pharmacogenes having a higher proportion of variants in malaria endemic areas (e.g., UGT1A9) may be necessary. Moreover, a high frequency in the functional variant of CYP2C8, rs11572103T>A (*2), was found in the South African population. This may also have relevance for future consideration of pharmacogenetic testing for a person traveling to malaria endemic areas from non-endemic areas, such as South Africa. Future studies should be done using large scale sequencing datasets from malaria endemic areas and assess the effect of common variants of antimalarial pharmacogenes on the safety and efficacy of currently used antimalarial drugs.