Unveiling the heritability of selected unexplored pharmacogenetic markers in the Saudi population

Pharmacogenomic (PGx) variants can significantly impact drug response, but limited data exists on their prevalence in Middle Eastern populations. This study aimed to investigate the inheritance of certain markers in candidate pharmacogenes among healthy Saudis.

DNA samples from 95 unrelated healthy Saudi participants were genotyped using the Affymetrix Axiom Precision Medicine Diversity Array. Thirty-eight variants in 15 pharmacogenes were analyzed based on their clinical relevance and lack of previous reporting in Saudi populations.

Twenty-six of the 37 tested markers were undetected in the cohort. The selected variants in six genes [DPYD (rs1801268), CACNA1S (rs772226819), EGFR (rs121434568), RYR1 (rs193922816), CYP2B6 (rs3826711), and MT-RNR1 (rs267606617, rs267606618, rs267606619)] were found to be non-existing among Saudis. In contrast, 11 variants and alleles in nine pharmacogenes were detected at varying frequencies. Notable findings included high frequencies of variants in ATIC [rs4673993, minor allele frequency (MAF) = 0.71)] and SLC19A1 (rs1051266, MAF = 0.48) affecting methotrexate efficacy. Three alleles were identified in CYP3A4, including a common (CYP3A4 rs2242480) and two rare alleles (*3 and *22). Another three markers [rs16969968 in CHRNA5, rs11881222 in IFNL3 (IL28B), and SLCO1B1*14] were found to be highly distributed among the participants (MAF = 0.35, 0.30, and 0.14, respectively). Conversely, three rare markers: CYP2A6*2, NAT2*14, and rs115545701 in CFTR, were identified at low-frequency levels (MAF = 0.021, 0.011, 0.005, respectively). Statistically significant differences in allele frequencies were observed for eight variants between Saudi and African populations, five variants compared to East Asians, and two variants compared to Europeans.

This study provides novel insights into the distribution of clinically relevant PGx variants in the Saudi population. The findings have implications for personalizing treatments for various conditions, including rheumatoid arthritis, cystic fibrosis, and hepatitis C. These data contribute to the development of population-specific PGx testing panels and treatment guidelines.