Abstract:The human cytochrome P450 (CYP) is a superfamily of enzymes that have been a focus in research for decades due to their prominent role in drug metabolism. CYP2C is one of the major subfamilies which metabolize more than 10% of all clinically used drugs. In the context of CYP2C19, several key genetic variations that alter the enzyme’s activity have been identified and catalogued in the CYP allele nomenclature database. In this study, we investigated the presence of well-established variants as well as novel pol… Show more
“…In general, the prevalence of rapid metabolizers and poor metabolizers was 38.5 and 19.9%, respectively. Our results agree with previous studies that reported a prevalence of rapid metabolizers of 65–78% for whites but only 30–40% for Asian populations, whereas the prevalence of poor metabolizers in Asian populations (13–23%) was higher than in whites (2–5%) [ 16 , 20 , 21 , 36 , 37 ]. Although studies on CYP2C19 polymorphisms in Indonesia are still scarce, the expected genotype distribution in this study showed the same pattern as another neighboring country in Southeast Asia (Thailand) and as other Asian countries, such as Korea, Japan, and China ( Supplementary Table S3 ).…”
CYP2C19 polymorphisms are important factors for proton pump inhibitor-based therapy. We examined the CYP2C19 genotypes and analyzed the distribution among ethnicities and clinical outcomes in Indonesia. We employed the polymerase chain reaction-restriction fragment length polymorphism method to determine the CYP2C19 genotypes and evaluated inflammation severity with the updated Sydney system. For CYP2C19*2, 46.4% were the homozygous wild-type allele, 14.5% were the homozygous mutated allele, and 39.2% were the heterozygous allele. For CYP2C19*3, 88.6% were the homozygous wild-type allele, 2.4% were the homozygous mutated allele, and 9.0% were the heterozygous allele. Overall, the prevalence of rapid, intermediate, and poor metabolizers in Indonesia was 38.5, 41.6, and 19.9%, respectively. In the poor metabolizer group, the frequency of allele *2 (78.8%) was higher than the frequency of allele *3 (21.2%). The Papuan had a significantly higher likelihood of possessing poor metabolizers than the Balinese (OR 11.0; P = 0.002). The prevalence of poor metabolizers was lower compared with the rapid and intermediate metabolizers among patients with gastritis and gastroesophageal reflux disease. Intermediate metabolizers had the highest prevalence, followed by rapid metabolizers and poor metabolizers. Dosage adjustment should therefore be considered when administering proton pump inhibitor-based therapy in Indonesia.
“…In general, the prevalence of rapid metabolizers and poor metabolizers was 38.5 and 19.9%, respectively. Our results agree with previous studies that reported a prevalence of rapid metabolizers of 65–78% for whites but only 30–40% for Asian populations, whereas the prevalence of poor metabolizers in Asian populations (13–23%) was higher than in whites (2–5%) [ 16 , 20 , 21 , 36 , 37 ]. Although studies on CYP2C19 polymorphisms in Indonesia are still scarce, the expected genotype distribution in this study showed the same pattern as another neighboring country in Southeast Asia (Thailand) and as other Asian countries, such as Korea, Japan, and China ( Supplementary Table S3 ).…”
CYP2C19 polymorphisms are important factors for proton pump inhibitor-based therapy. We examined the CYP2C19 genotypes and analyzed the distribution among ethnicities and clinical outcomes in Indonesia. We employed the polymerase chain reaction-restriction fragment length polymorphism method to determine the CYP2C19 genotypes and evaluated inflammation severity with the updated Sydney system. For CYP2C19*2, 46.4% were the homozygous wild-type allele, 14.5% were the homozygous mutated allele, and 39.2% were the heterozygous allele. For CYP2C19*3, 88.6% were the homozygous wild-type allele, 2.4% were the homozygous mutated allele, and 9.0% were the heterozygous allele. Overall, the prevalence of rapid, intermediate, and poor metabolizers in Indonesia was 38.5, 41.6, and 19.9%, respectively. In the poor metabolizer group, the frequency of allele *2 (78.8%) was higher than the frequency of allele *3 (21.2%). The Papuan had a significantly higher likelihood of possessing poor metabolizers than the Balinese (OR 11.0; P = 0.002). The prevalence of poor metabolizers was lower compared with the rapid and intermediate metabolizers among patients with gastritis and gastroesophageal reflux disease. Intermediate metabolizers had the highest prevalence, followed by rapid metabolizers and poor metabolizers. Dosage adjustment should therefore be considered when administering proton pump inhibitor-based therapy in Indonesia.
“…A Sinhalese population also showed a higher prevalence of the *2 allele (44.7%) 89. A North Asian population and an Orang Asli indigenous population of Malaysia showed lower *2 allele prevalence (18.5% and 5.7%, respectively) than either East Asians or South/Central Asians 70,90…”
Section: Resultsmentioning
confidence: 93%
“…They are intended for the visualization of the complexity of ethnic categorization in pharmacogenetics literature and only reflect how these ethnic categories were classified in the literature we reviewed. A full list of ethnic categories included in this study can be found in Table S2 .Figure 1Chart of ethnic categories which fall under the NIH term of “Asian”. Note: Data from references 7, 8, 10, 12, 14, 16, 28, 37, 41, 42, 48, 51, 71–73, 87–90.Figure 2Chart of ethnic categories which fall under the NIH term of “Caucasian”. Note: Data from references 9, 11, 13, 18, 20–26, 28, 34, 37, 42–45, 70, 75, 87, 91–94, 128.Figure 3Chart of ethnic categories which fall under the NIH term of “Black”. Note: Data from references 11, 15, 16, 19, 26–33, 35–37, 40, 46, 47, 49, 50, 70, 75, 79, 87, 94–97, 129, 130.…”
Introduction
Racial and ethnic categories are frequently used in pharmacogenetics literature to stratify patients; however, these categories can be inconsistent across different studies. To address the ongoing debate on the applicability of traditional concepts of race and ethnicity in the context of precision medicine, we aimed to review the application of current racial and ethnic categories in pharmacogenetics and its potential impact on clinical care.
Methods
One hundred and three total pharmacogenetics papers involving the
CYP2C9, CYP2C19
, and
CYP2D6
genes were analyzed for their country of origin, racial, and ethnic categories used, and allele frequency data. Correspondence between the major continental racial categories promulgated by National Institutes of Health (NIH) and those reported by the pharmacogenetics papers was evaluated.
Results
The racial and ethnic categories used in the papers we analyzed were highly heterogeneous. In total, we found 66 different racial and ethnic categories used which fall under the NIH race category “White”, 47 different racial and ethnic categories for “Asian”, and 62 different categories for “Black”. The number of categories used varied widely based on country of origin: Japan used the highest number of different categories for “White” with 17, Malaysia used the highest number for “Asian” with 24, and the US used the highest number for “Black” with 28. Significant variation in allele frequency between different ethnic subgroups was identified within 3 major continental racial categories.
Conclusion
Our analysis showed that racial and ethnic classification is highly inconsistent across different papers as well as between different countries. Evidence-based consensus is necessary for optimal use of self-identified race as well as geographical ancestry in pharmacogenetics. Common taxonomy of geographical ancestry which reflects specifics of particular countries and is accepted by the entire scientific community can facilitate reproducible pharmacogenetic research and clinical implementation of its results.
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