The health burden resulting from parasitic and infectious diseases such as HIV/AIDS, tuberculosis and malaria, requires that available medication and limited healthcare resources be used optimally. However, due to co-morbidities, patients are often exposed to many drugs concurrently. Most of these drugs are metabolised by similar enzymes which are polymorphic, thus, drug-drug interactions are a constant problem. Quantitative and qualitative differences in drug metabolizing enzyme variants in different populations result in differential drug response. This study investigated the baseline frequencies of genetic variants in key drug metabolizing cytochrome P450 enzymes, CYP1A2, CYP2A6, CYP2B6, CYP3A4 and CYP3A5 in two previously understudied Bantu-speaking populations from Cameroon (N=72) and South Africa (N=163) using PCR-RFLP. Genotype frequencies for CYP1A2 C-163A and CYP3A4 A-392G single nucleotide polymorphisms (SNPs) were significantly different between these two populations (P=0.0004 and 0.0079, respectively). Significant differences were also observed when the two Bantu-speaking populations were each compared to other African populations as well as Caucasian and Asian populations. Importantly, correspondence analysis showed that the two Bantu-speaking African populations were separated from each other and from other African populations based on CYP1A2 C-163A and CYP2A6 G1093A SNPs. The data show that drugs that are substrates for these polymorphic enzymes are likely to have different response profiles among the Bantu-speaking populations and populations of either Caucasian or Asian origin, further emphasizing the need to genetically characterise as many African populations in order to realize personalised medicine. These data further emphasize that linguistically related Bantu-speaking populations are not necessarily genetically homogenous. Finally, we note that our observations also inform future pharmacogeneticguided rational therapeutic drug monitoring to prevent or minimize the risk for adverse drug-drug interactions mediated by these genetically polymorphic pathways.
Keywords: Bantu-speaking population, Cameroon, correspondence analysis, cytochrome P450, global pharmacogenetics, population pharmacogenetics, public health genomics, South Africa