Pharmcogenomics of human drug response: roles of NAT2 and CY2C8 in anti-malarial drug therapy in Mutengene, South West Region-Cameroon

Claude Marcelle Njiki
Biochemistry, University of Yaounde I
June, 2018
 

Abstract

INTRODUCTION: Malaria continues to be endemic despite several efforts for its eradication.. The persistence and increase of both incidence and mortality rates over the years was as because of ineffective, failing Chloroquine, Amodiaquine and Sulphadoxine Pyrimethamine monotherapies led to the implementation of Artemisinin Combination Therapies (ACTs) by the WHO. Though proven to be very effective, resistances were documented across South East Asia. Clinical trials have shed more light on the existence of poor treatment outcome despite efficient ACT treatment. They revealed that individuals could either be slow, intermediate or fast metabolizers due to diverse genetic status. This genetic diversity causes large variability in the pharmacokinetic profiles of many antimalarial drugs and varied concentrations of antimalarial drugs in plasma leading to either sub-optimal or optimal effectiveness in some patients. Some drug metabolising enzymes, predominantly cytochrome P450 (termed oxidative) and NAT2 (N-acetyl transferase 2) (termed conjugative) enzymes, contribute to drug response and hence treatment outcomes. CYP2C8 of the human CYP2C subfamily is mainly responsible for the metabolism of the antimalarial Amodiaquine which is now commonly used as a selective marker activity. Any genetic polymorphisms involving CYP2C8 and NAT2 tends to affect drug metabolism leading to individuals either being slow, intermediate or fast metabolisers.

OBJECTIVE: To determine CYPC28 and NAT2 mutations clustering with treatment outcome.

METHODS: Archival samples from 72 patients in Mutengene with parent-given consent, all respecting the inclusion criteria were enrolled for the study. They were randomly treated with
Arthemeter Lumefantrine, Dihydroartemisinin piperaquine and Artesunate-Amodiaquine for 3days, then followed up for 28 days to assess treatment outcomes. Blood samples from all patients were collected and stored on filter paper from which DNA was extracted using the Chelex method. The DNA extracts were used during PCR- RFLP with restriction enzymes BClI for the detection of single nucleotide polymorphisms in the CYP2C8 gene and BamHI, KpnI and TaqI for the detection of single nucleotide polymorphisms in the NAT2 gene, notably; NAT2*5, NAT2*7, and NAT2*6, respectively. Data collected was analysed using International Business Machine Statistical Package for Social Sciences (SPSS) version 20. A p-value of 0.05 was set as the threshold for statistical significance with a confidence interval of 95%.

RESULTS: Concerning NAT2 the most prevalent genotype was NAT2*5/6, accounting for 22.20% and slow phenotype (48.61%) being the predominant paramount phenotype in Mutengene. The different treatment outcomes encountered were; early treatment failure and adequate clinical and parasitological response. Fast metabolisers were much more liable to suffer from early treatment failure (OR=3.358; P-value=0.276) with respect to slow metabolizers. Slow metabolisers were more liable to develop adverse events (OR=2.800; P-value=0.54). CYP2C8*1/1 was the most prevalent genotype (75%), fast metabolisers being the predominant phenotype. Fast metabolisers were more liable to succumb to early treatment failure (OR= 0.951; P-value=0.603). Slow metabolisers were more liable to ACPR (OR=1.918; P-value=0.279). The fast metabolisers were more prone to adverse drug events (OR= 0.951; P-value=0.603).

CONCLUSION: CYP2C8*1/1 was the most prevalent genotype, fast metabolisers were more likely to have early treatment failure as well as presenting adverse drug events. NAT2*5/6 was the most common NAT2genotype. Fast metabolisers are prone to have early treatment failure. Slow metabolisers were liable to ACPR and adverse drug events.


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