CYP2C:TG Haplotype in Native Mexicans, Molecular Ancestry and Its Implications for CYP2C19 Genotype–Phenotype Correlation

<b>Background:</b> Recent studies have associated the presence of the <i>CYP2C</i>:<i>TG</i> haplotype with increased metabolism of CYP2C19 substrates such as escitalopram and sertraline, suggesting a potential regulatory interaction between <i>CYP2C18</i> and <i>CYP2C19</i>. However, this association has not been demonstrated for other CYP2C19 substrates. <b>Objective:</b> This study aims to elucidate the role of the <i>CYP2C</i>:<i>TG</i> haplotype in modulating CYP2C19 activity using the omeprazole metabolic ratio (MR) within a cocktail drug approach, to characterize its distribution and prevalence among Native Mexican populations, and to evaluate its potential impact on CYP2C19 metabolic phenotypes. <b>Materials and Methods:</b> A total of 256 volunteers from various ethnic native groups from Mexico were genotyped for <i>CYP2C19</i> (<i>*2</i>, <i>*3</i>, <i>*4</i>, <i>*5</i>, <i>*17</i>) and the <i>CYP2C</i> haplotype (rs2860840 and rs11188059). The MR of omeprazole to 5-hydroxyomeprazole was analyzed to determine individual CYP2C19 metabolic phenotypes and assess metabolic capacity. <b>Results:</b> The <i>CYP2C</i>:<i>TG</i> haplotype was the most prevalent (42.77%), followed by <i>CYP2C</i>:<i>CG</i> (35.74%) and <i>CYP2C</i>:<i>TA</i> (21.48%). The <i>CYP2C</i>:<i>TG</i> haplotype was consistently associated with the <i>CYP2C19*1</i> allele. Significant differences in logMR values were observed between individuals with and without the <i>TG</i> haplotype (<i>p</i> = 0.02). A trend toward increased metabolic activity associated with <i>CYP2C</i>:<i>TG</i> was observed across most CYP2C19 metabolizer groups, except for rapid metabolizers. No significant association was found between molecular ancestry and the presence or functionality of the haplotype. <b>Conclusions:</b> The <i>CYP2C</i>:<i>TG</i> haplotype appears to be associated with increased CYP2C19 activity, warranting further functional validation before clinical implementation.