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The Diversity of CYP2C19 polymorphisms in Thai Population | TACG
Vorthunju Nakhonsri,1 Shobana John,2,3 Hathaichanok Panumasmontol,4,5 Manassanan Jantorn,4,5 Pongpipat Chanthot,4,5 Nuntachai Hanpramukkun,6 Supaporn Meelarp,7 Chonlaphat Sukasem,2,3 Sissades Tongsima,1 Sukhontha Hasatsri,4 Abhisit Prawang,8 Thanawat Thaingtamtanha,9,10 Natchaya Vanwong,11,12 Chalirmporn Atasilp,13 Monpat Chamnanphon,14 Pimonpan Jinda,2,3 Patompong Satapornpong4,5
1National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathum Thani, Thailand; 2Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; 3Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center (SDMC), Ramathibodi Hospital, Bangkok, Thailand; 4Division of General Pharmacy Practice, Department of Pharmaceutical Care, College of Pharmacy, Rangsit University, Pathum Thani, Thailand; 5Excellence Pharmacogenomics and Precision Medicine Centre, College of Pharmacy, Rangsit University, Pathum Thani, Thailand; 6Division of Pharmaceutical Technology, Department of Industrial Pharmacy, College of Pharmacy, Rangsit University, Pathum Thani, Thailand; 7Ounjai Medical Clinic, Bangsue, Bangkok, Thailand; 8Division of Pharmacy Practice, Department of Pharmaceutical Care, College of Pharmacy, Rangsit University, Pathum Thani, Thailand; 9Department of Chemistry and Biology, University of Siegen, Siegen, Germany; 10Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa, ON, Canada; 11Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, Thailand; 12Department of Clinical Chemistry, SYstems Neuroscience of Autism & PSychiatric Disorders (SYNAPS) Research Unit, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, Thailand; 13Chulabhorn International College of Medicine, Thammasat University, Pathumthani, Thailand; 14Department of Pathology, Faculty of Medicine, Srinakharinwirot University, Nakornnayok, Thailand
Correspondence: Patompong Satapornpong, Director of Excellence Pharmacogenomics and Precision Medicine Centre, College of Pharmacy, Rangsit University, Pathum Thani, Thailand, Tel +66- 2-791-6000 1420, Fax +66- 2-791-6000 1403, Email [email protected]
Introduction: CYP2C19 plays a major role in the metabolism of various drugs. The most common genetic variants were the CYP2C19*2 and *3 alleles (rs4244285 and rs4986893, non-functional variants). In previous studies, we found that genetic polymorphisms in CYP2C19 variants influenced the active metabolites of clopidogrel and caused major adverse cardiovascular and cerebrovascular effects. However, the distribution of CYP2C19 varies among ethnic groups and according to adverse drug reactions. This study aimed to investigate the frequency of CYP2C19 genetic polymorphisms in the Thai population and analyze the differences in the frequency of CYP2C19 genetic polymorphisms between Thai and other populations.
Methods: This study enrolled 211 unrelated healthy Thai individuals in total. We performed a real-time polymerase chain reaction to genotype CYP2C19*2 (681G > A) and CYP2C19*3 (636G > A).
Results: In the Thai population, the CYP2C19*1 allele was the most prevalent at 70.14%, while the CYP2C19*2 and *3 alleles were found at frequencies of 25.36% and 4.50%, respectively. Conversely, the CYP2C19*3 allele was not detected in Caucasian, Hispanic, African, Italian, Macedonian, Tanzanian, or North Indian populations. The phenotypic profile of this gene revealed that the frequency of intermediate metabolizers (IMs) is nearly equal to that of extensive metabolizers (EMs), at 42.65% and 48.82% respectively, with genotypes *1/*2 (36.02%) and *1/*3 (6.63%). Likewise, poor metabolizers (PMs) with genotypes *2/*2 (6.16%), *2/*3 (2.37%), and *3/*3 (Conclusion: The distribution of CYP2C19 genotype and phenotype influenced by non-functional alleles has potential as a pharmacogenomics biomarker for precision medicine and is dependent on an ethnic-specific genetic variation database.
Keywords: CYP2C19 gene, genetic diversity, Thai population, interethnic differences
Introduction
Cytochrome P450 (CYP) proteins form a superfamily of enzymes that are involved in the metabolism of drugs, fatty acids, steroids, and xenobiotics.1,2 Research has demonstrated that the metabolic activity of CYP enzymes is influenced by genetic polymorphisms.3,4 These polymorphisms in drug-metabolizing enzyme genes contribute to variations in pharmacological responses and the risk of adverse drug events among individuals and across different ethnic groups.5 The human CYP2C subfamily includes four members: CYP2C8, CYP2C9, CYP2C18, and CYP2C19.6
The CYP2C19 gene is located on chromosome 10 (10q24.1-q24.3) and is responsible for approximately 10% of drug metabolism in clinical practice.7,8 CYP2C19 plays a crucial role in metabolizing various therapeutic drugs, including clopidogrel, phenytoin, omeprazole, proguanil, diazepam, citalopram, imipramine, amitriptyline, and clomipramine.9 The most common genetic variant of CYP2C19 is the CYP2C19*2 allele (rs4244285, c. G681A), a single base pair mutation in exon 5 that results in a splicing defect, impairing enzyme function.10 Another significant variant, CYP2C19*3 (rs4986893), is a G636A mutation in exon 4, producing a premature stop codon.11 CYP2C19 genotypes and phenotypes are categorized as follows: *1/*1 (extensive metabolizers, EMs, two functional alleles); *1/*2 and *1/*3 (intermediate metabolizers, IM, one null allele and one functional allele); and *2/*2, *2/*3, and *3/*3 (poor metabolizers, PM, two non-functional alleles).12–14 Numerous studies have shown a correlation between CYP2C19 polymorphisms and enzyme activity in patients treated with relevant drugs.15–17
Clopidogrel is commonly used to treat myocardial infarction (MI), stroke, acute coronary syndrome (ACS), and atherosclerotic vascular disease.18 Notably, CYP2C19 plays a crucial role in converting clopidogrel into its active metabolite, clopi-H4.19 This active metabolite inhibits the adenosine diphosphate P2Y12 receptor, thereby reducing platelet activation. According to the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for clopidogrel, alleles associated with the CYP2C19 poor metabolizers phenotype (*2/*2, *2/*3, and *3/*3) are significantly linked to lower levels of active clopidogrel metabolites and an increased risk of major adverse cardiovascular and cerebrovascular events.20 Furthermore, the CYP2C19 intermediate metabolizers (IMs) phenotype also reduces the effectiveness of clopidogrel.
The distribution of poor metabolizers (PMs) with genotypes *2/*2, *2/*3, and *3/*3 vary among different populations. The highest prevalence is observed in East Asians (12.97%) and Asians (8.15%), followed by African Americans (4.05%) and Europeans (2.38%). A similar pattern is seen with intermediate metabolizers (IMs), with East Asians having the highest frequency (45.92%), followed by Asians (40.80%), African-Americans (31.39%), and Europeans (26.10%).21 These genetic variations in CYP2C19 across different ethnicities are crucial for understanding individual differences in treatment effectiveness and safety, especially in the context of pharmacogenomics-based dosing guidelines. Consequently, this study aimed to investigate the prevalence of CYP2C19 genetic variations in the Thai population and compare them with those in other populations.
Materials and Methods
Thai Subjects
This cross-sectional study recruited 211 unrelated, healthy individuals of Thai ethnicity, with clinical data obtained from the Excellence Pharmacogenomics and Precision Medicine Centre, College of Pharmacy, Rangsit University, between November 2021 and February 2023 (Supplement 1). All participants were native Thais who were lived in the location of Thailand and had no history of adverse drug reactions (ADRs). We used self-identified race/ethnicity (SIRE) method to confirm the ethnicity, specifically three generations were confirmed as Thais. Thailand is centrally located in Mainland Southeast Asia, bordered by Myanmar to the west, Laos to the northeast, Cambodia to the east, and Malaysia to the south. The study received approval from the Ethics Review Board of Rangsit University (COA. No. RSUERB2021-104), and according to the Declaration of Helsinki with a written informed consent was obtained from all participants.
CYP2C19 Genotyping
Genomic DNA was extracted from EDTA whole blood using a Geneaid DNA Isolation Kit (Geneaid Biotech Ltd., New Taipei City, Taiwan). The quality and quantity of the genomic DNA were measured using an ultraviolet-visible spectrophotometer (Zhengzhou, Henan, China). Genotyping of CYP2C19*2 (681G > A, rs4244285, non-functional variant) and CYP2C19*3 (636G > A, rs4986893, non-functional variant) was performed using TaqMan assays (C__30634128_10 and C__27861809_10 respectively; ABI, Foster City, CA, USA). The PCR cycling conditions included 50 cycles of denaturation at 92°C for 15 seconds, and annealing and extension at 60°C for 1.30 minutes. CYP2C19 variants were identified using a QIAGEN QIAquant 96 real-time PCR system (Qiagen, Hilden, Germany).
CYP2C19 Phenotype
According to the Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline, CYP2C19*1/*1 is categorized as an extensive metabolizers (EMs) with two normal-function alleles. Intermediate metabolizers (IMs) have one normal and one non-functional allele (CYP2C19*1/*2 and CYP2C19*1/*3). Poor metabolizers (PMs) carry two non-functional alleles (CYP2C19*2/*2, CYP2C19*2/*3, and CYP2C19*3/*3).
Statistical Analysis
The frequencies of the two common CYP2C19 variants were analyzed using the Arlequin program version 3.1 for Hardy–Weinberg equilibrium testing. Allele and phenotype frequencies of CYP2C19 in the Thai population were compared with those in other populations using R Statistical Software (v4.1.2; R Core Team 2021). Odds ratios for all comparisons were illustrated in a forest plot using the Meta for R package (v4.2.0; Viechtbauer 2010). A significant difference was identified for each population compared with the Thai population if the p-value was less than 0.05.
Results
The Frequency of CYP2C19 Alleles in Thai Population
A total of 211 unrelated healthy Thai participants were included in this study, comprising fifty-five males (26.07%) and one hundred fifty-six females (73.93%). The mean age of the participants was 38.3 years, ranging from 19 to 75 years. We determined the allele frequency distribution of CYP2C19 in the Thai population (Table 1). The CYP2C19*1 allele was the most common, with a frequency of 70.14%. The frequencies of the CYP2C19*2 and CYP2C19*3 alleles were 25.36% (n = 107) and 4.50% (n = 19), respectively. Among the healthy Thai participants, the CYP2C19 genotypes were distributed as follows: 103 (48.82%) were extensive metabolizers (EMs, CYP2C19*1/*1), 76 (36.02%) were intermediate metabolizers (IMs, *1/*2 and *1/*3), and 14 (6.63%), 13 (6.16%), and 5 (2.37%) were poor metabolizers (PMs, *2/*2 and *2/*3). The frequency of the CYP2C19*3/*3 (PMs) genotype was less than 1.00% of the total Thai population. The allele frequencies of CYP2C19*2 and *3 were tested for Hardy–Weinberg equilibrium (p-value
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Table 1 Alleles and Genotyping Frequencies for CYP2C19 Genes in the Thai Population (n = 211) |
Comparative of CYP2C19 Genotype and Phenotype Frequency Between the Thai and Other Populations
The frequencies of the CYP2C19*2 and *3 alleles were evaluated in Thai and various other populations, as shown in Tables 2 and 3 and Figure 1A and B. This study found that the CYP2C19*2 allele was particularly frequent. The highest frequencies of the CYP2C19*2 allele were observed in Indians (37.90%),30 Native Japanese (34.50%),33 and Bhutanese (30.14%),34 followed by North Indians (29.75%),29 Koreans (28.40%),33 Thais (25.36%), Han Chinese (24.67%),31 Vietnamese (20.50%),35 and Africans (20.20%)26 (Table 2 and Figure 1A). Conversely, the Bhutanese population had the highest observed frequency of the CYP2C19*3 allele (15.69%)34 (Table 3 and Figure 1B). High distributions of the CYP2C19*3 allele were also observed in Koreans (10.10%),33 Native Japanese (9.00%),32 Malaysians (6.50%),36 and Thais (4.50%), while the CYP2C19*3 allele was not found in Caucasian, Hispanic, African, Italian, Macedonian, Tanzanian, and North Indian populations.22–26,28,29
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Table 2 The Allele Frequencies of CYP2C19*2 in Many Populations |
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Table 3 The Allele Frequencies of CYP2C19*3 in Many Populations |
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Figure 1 Forest plot displaying the odds ratios for the frequencies of CYP2C19*2 (A) and CYP2C19*3 (B) alleles across multiple populations in comparison to the Thai population allele frequency. |
A comparison of CYP2C19*2 and *3 frequencies between the Thai population and other populations is presented in Tables 2 and 3 and Figure 1A and B. The distribution of CYP2C19 variations was similar among the Thai, Han Chinese, Vietnamese, and Venezuelan populations (p-value > 0.05). However, the CYP2C19*2 allele showed significant differences between the Thai population and others, such as Italian (p-value = 1.21×10−5), Macedonian (p-value = 0.0056), Caucasian (p-value = 0.0176), Hispanic (p = 6.04×10−5), Indian (p-value = 0.0298), and Malaysian populations (p-value = 0.0007). A strong significant difference was also observed for CYP2C19*3 frequencies when comparing Thai with Bhutanese and Hispanic populations (p-value = 8.94×10−6 and 1.58 x 10−5, respectively).
Phenotyping of CYP2C19*1/*1 (extensive metabolizers, EMs) was highly prevalent in several populations (Table 4 and Figures 2 and 3). The highest frequencies of CYP2C19*1/*1 were observed in the Italian population (79.44%) compared to the Thai population (p-value = 8.22×10−14).22 Intermediate metabolizers (CYP2C19 *1/*2 and *1/*3) showed the following phenotype distribution: Italian (18.89%), Macedonian (19.02%), Caucasian (18.52%), Hispanic (18.00%), African (19.19%), African-American (23.60%), and Malaysian (14.52%) populations.22–26,36 Significant differences in IMs prevalence were observed when compared with Thais (p-value −20).34
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Table 4 Phenotyping Frequencies of CYP2C19*2 and *3 Polymorphism Among Different Ethnicities Compared with Thai Population |
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Figure 2 Forest plot displaying the odds ratios for the frequencies of CYP2C19 intermediate metabolizers (IMs; *1/2 + *1/3) diplotypes (A) and CYP2C19 poor metabolizers (PMs; *2/*2 + *2/*3 + *3/*3) diplotypes (B) across multiple populations in comparison to the Thai population diplotype frequency. |
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Figure 3 Distribution of CYP2C19 polymorphisms in Thais and ethnic groups. |
The distribution of poor metabolizers (PMs) of CYP2C19 (*2/*2, *2/*3, and *3/*3) was 19.00% in Native Japanese,32 14.02% in Koreans,33 10.42% in Han Chinese,31 9.82% in Indians,30 8.53% in Thais, 7.44% in North Indians,29 6.32% in Bhutanese,34 6.06% in Africans,26 4.84% in Malaysians,36 4.63% in Venezuelans,27 4.40% in African-Americans,25 4.17% in Caucasians,24 4.00% in Vietnamese,35 3.77% in Tanzanians,28 2.72% in Macedonians,23 1.67% in Italians,22 and 1.60% in Hispanics.25 The PMs prevalence was significantly higher in Thai patients compared to Italian (p-value = 0.0001), Macedonian (p-value = 0.0168), and Hispanic (p-value = 0.0006) patients. Conversely, the PMs prevalence in the Thai population was lower than in the Native Japanese population (OR = 2.51, 95% CI = 1.34–4.86, p-value = 0.0024). The odds ratios for these comparisons are illustrated in Figure 2A and B using forest plots.
Discussion
According to the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, the CYP2C19 gene is a significant pharmacogenomic polymorphism in various populations.20,37 In clinical settings, CYP2C19 plays a pivotal role in metabolizing approximately 8–10% of commonly used medications, including proton pump inhibitors, anticonvulsants, antiplatelet agents, and antidepressants.14,24 Notably, patients carrying homozygous alleles (PMs) and heterozygous alleles (IMs) of CYP2C19*2 and *3 variants are reported to have approximately 1.8-fold and 1.5-fold increased risk, respectively, of developing severe adverse cardiovascular events (e.g.death, myocardial infarction, stroke) following clopidogrel treatment.38,39 Thus, non-functional CYP2C19 variants significantly impact the dosage requirements for clopidogrel therapy in individual patients.
In our study, the most prevalent non-functional variant was the CYP2C19*2 allele, found in approximately 25.36% of our sample, consistent with previous reports in various populations, including Asian populations (Han Chinese, Native Japanese, Korean, Bhutanese, Vietnamese, and North Indians), Africans, African-Americans, Venezuelans, and Tanzanians.25–28,31–36 In contrast, Caucasian, Hispanic, Macedonian, and Italian populations exhibited lower frequencies of the CYP2C19*2 allele compared to the Thai population.22–25 However, these variations were attributed to the distribution of non-functional CYP2C19 alleles in each population and their impact on clopidogrel efficacy. Further investigations are necessary to confirm the influence of CYP2C19*2 distribution across ethnicities and the effects on clinically relevant medications.
The allele frequency of CYP2C19*3 (c C806T) in our study was approximately 4.50%, similar to earlier reports in the Thai population.40 Additionally, the frequency of CYP2C19*3 in Han Chinese was 3.27%, consistent with other Asian populations, as shown in Table 3 and Figure 1B. Interestingly, the distribution of CYP2C19*3 in these Asian populations, including Thai, closely resembled each other, except for Bhutanese, Korean, and North Indian populations. Specifically, we observed a higher distribution of CYP2C19*3 in the Bhutanese population compared to the Thai population (p-value = 8.94×10−6). However, the prevalence of the CYP2C19*3 allele was absent in Italian, Macedonian, Caucasian, Hispanic, African, Tanzanian, and North Indian populations.22–26,28,29 This genetic variability across racial and ethnic groups underscores the importance of CYP2C19*3 allele frequency as a pharmacogenomics marker for screening different ethnicities to prevent therapeutic failures in individual patients, particularly in the Asian population.
None of the Thai participants in our study carried the homozygous CYP2C19*3/*3 allele. However, PMs phenotypes based on CYP2C19*2/*2 and *2/*3 genotypes were present in approximately 6.16% and 2.37% of the sample, respectively. Our findings align with previous research indicating a PMs distribution of approximately 19% in Asian populations compared to around 2% in Caucasians.41 Notably, substantial variation in the distribution of these CYP2C19 genotypes was observed across populations, with less than 1% occurrence of these variants (*1/*3, *2/*3, and *3/*3) in European and African American populations, contrasting with frequencies of *1/*3 (7.34%), *2/*3 (3.33%), and *3/*3 (0.44%) in East Asian populations.42 Given the genetic diversity of CYP2C19 variants across ethnicities, determining the CYP2C19*3 genotype and phenotype before treatment initiation is particularly advantageous for Asian populations. Moreover, the understanding of CYP2C19 polymorphisms can significantly impact patient prognosis and outcomes, particularly in the context of drugs like clopidogrel, where genetic variations affect drug metabolism and efficacy. However, the relationship between CYP2C19 phenotype frequency and drug efficacy or adverse drug reactions (ADRs) warrants further investigation in other populations.
Conversely, the CYP2C19*17 variant (c. −806C>T) demonstrates ultra-rapid CYP2C19 activity and holds a significant role in the metabolic pathways of therapeutic drugs, which could heighten the risk of treatment failure with this substrate. From a clinical standpoint, the CYP2C19*17 variant strongly correlates with an increased risk of clopidogrel-induced bleeding in patients with cardiovascular and cerebrovascular diseases (OR = 1.89, 95% CI: 1.09–3.25, p-value = 0.02). This association is attributed to the heightened transcriptional activity of the CYP2C19 enzyme and its exaggerated response to clopidogrel’s prodrug.43 Conversely, this variant exhibits a notable association with a reduced risk of major adverse cardiovascular and cerebrovascular events in patients with coronary artery disease (OR = 0.76, 95% CI: 0.60–0.98, p = 0.03).43 Furthermore, the CYP2C19*17 genotype has been observed at higher frequencies among European and African populations, approximately 15.0–25.0%, whereas the Asian population exhibits a much lower frequency, approximately 4%.44 Given these trends, further exploration of the frequency of CYP2C19*17 variants and their association with adverse drug reactions is warranted across various populations.
One limitation of our study stems from the genotyping method employed for CYP2C19. We utilized real-time PCR to detect two single nucleotide polymorphisms (SNPs), rs4244285 (*2) and rs4986893 (*3). In cases where individuals did not carry these two variants, we presumed the genotype to be *1. However, this assumption may not accurately represent the true *1 status, as other untested variants could be present. This methodological approach has the potential to affect the precision of our genotyping Results and subsequent interpretations of CYP2C19 metabolic phenotypes. While real-time PCR is a highly reliable technique, the importance of validation cannot be overstated. To mitigate this concern, future studies should consider validating genotyping results using DNA sequencing methods, which offer a more comprehensive analysis of CYP2C19 variants and minimize potential errors. By integrating such validation steps, we can enhance the accuracy of genotyping and ensure a more dependable identification of metabolic phenotypes, thereby enhancing the relevance of our findings in clinical practice. In future research, we plan to include clinical data to investigate how these genetic variations impact drug response and adverse reactions in real-world scenarios.
In conclusion, the distribution of the CYP2C19 gene via non-functional alleles holds promise for implementation in clinical practice and relies on an ethnic-specific genetic variation database. Specifically, the genotype and phenotype of CYP2C19*3 could serve as a pharmacogenomics biomarker in Thai and Asian populations for screening, mitigating genetic associations with adverse drug reactions induced by certain medications.
Acknowledgments
This study was supported by grants from the (1) College of Pharmacy, Rangsit University; (2) Research Institute of Rangsit University (64/2563); (3) Doctor Kasem Foundation (049/2565); and (4) Thailand Center of Excellence for Life Sciences (TCELS) (TC 24/63), Thailand. The authors thank the study participants and staff of the Excellence of Pharmacogenomics and Precision Medicine Centre, College of Pharmacy, Rangsit University, National Biobank of Thailand (NBT) and Pharmacogenomics and Personalized Medicine of Ramathibodi Hospital, Mahidol University.
Disclosure
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest or financial conflict with the subject matter or materials discussed in this manuscript.
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