Genetic profiling of CYP3A4 variants influencing carbamazepine metabolism and their gender-specific association among patients with epilepsy in Khyber Pakhtunkhwa
DOI:
https://doi.org/10.59736/IJP.22.04.928Keywords:
Carbamazepine, CYP3A4 polymorphism, Minor Allele frequency, Sanger sequencingAbstract
Background: Cytochrome P450 plays a pivotal role in metabolizing drugs, hormones, and vitamins with genetic variability influencing enzymatic activity. Genetic consortiums categorize variables such as CYP3A4-rs2242480 and rs2740574 as third-level evidence, indicating the need for further research into their health implications and pharmacogenetic relevance in carbamazepine metabolism. This study explores the distribution patterns of selected genes and their correlation with gender in our study population, aiming to advance personalized treatment approaches.
Methods: Using Sanger sequencing, Pashtun patients diagnosed with epilepsy and treated with carbamazepine monotherapy were genotyped for CYP3A4-rs2242480 and rs2740574 polymorphisms. The genetic variations were identified through Finch TV and analyzed for gender correlations.
Results: Minor Allele Frequency (MAF) of CYP3A4-rs2242480 and rs2740574 in 223 Pashtun patients with epilepsy was 27.8% and 1.7%, respectively. The genotype frequency of CYP3A4-rs2242480 was as follows: CC at 53.8%, with females 35% & males 65%; CT at 36.7%, with females 36.5% & males 63.4%; and TT at 9.4%, with females 47.6% & males 52.3%. For CYP3A4-rs2740574, the genotype frequencies were 0% CC, 3.6% CT, and 96.4% TT. Among individuals with the CT genotype, the distribution was evenly split between males (50%) and females (50%). For those carrying the TT genotype, females comprised 36.2% of the group, while males made up 63.7%.
Conclusion: The study uncovered genotype distributions of carbamazepine-metabolizing enzymes in the previously unexplored Pashtun population, revealing significant differences in CYP3A4-rs2740574 and rs2242480 frequencies compared to global ethnic groups. Also, no significant association was observed between genotype distribution patterns across genders.
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