Author:
Zdesenko Grace,Mduluza Takafira,Mutapi Francisca
Abstract
Schistosomiasis is a parasitic disease infecting over 236 million people annually, with the majority affected residing on the African continent. Control of this disease is reliant on the drug praziquantel (PZQ), with treatment success dependent on an individual reaching PZQ concentrations lethal to schistosomes. Despite the complete reliance on PZQ to treat schistosomiasis in Africa, the characterization of the pharmacogenetics associated with PZQ metabolism in African populations has been sparse. We aimed to characterize genetic variation in the drug-metabolising cytochrome P450 enzymes (CYPs) and determine the association between each variant and the efficacy of PZQ treatment in Zimbabwean patients exposed to Schistosoma haematobium infection. Genomic DNA from blood samples of 114 case-control Zimbabweans infected with schistosomes were sequenced using the CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 genes as targets. Bioinformatic tools were used to identify and predict functional effects of detected single nucleotide polymorphisms (SNPs). A random forest (RF) model was then used to assess SNPs most predictive of PZQ efficacy, with a misclassification rate of 29%. SNPs were detected across all six genes, with 70 SNPs identified and multiple functional changes to the CYP enzymes predicted. Only four SNPs were significantly associated with PZQ efficacy using χ2 tests, with rs951840747 (OR: 3.61, p = 0.01) in the CYP1A2 gene having the highest odds of an individual possessing this SNP clearing infection, and rs6976017 (OR: 2.19, p = 0.045) of CYP3A5 determined to be the most predictive of PZQ efficacy via the RF. Only the rs28371702 (CC) genotype (OR: 2.36, p = 0.024) of CYP2D6 was significantly associated with an unsuccessful PZQ treatment. This study adds to the genomic characterization of the diverse populations in Africa and identifies variants relevant to other pharmacogenetic studies crucial for the development and usage of drugs in these populations.
Subject
Genetics (clinical),Genetics,Molecular Medicine
Cited by
5 articles.
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