Table of Contents  

Al-Jaibeji, John, Al-Gazali, Soliman, Oulhaj, Katsila, Brand, Patrinos, and Ali: Allele and genotype frequencies of the two single nucleotide polymorphisms in the VKORC1 gene that are most important for warfarin treatment among Emiratis


Warfarin has been the most widely prescribed oral anticoagulant worldwide for the last 60 years. This is largely because of its effectiveness, low cost and convenient oral dose.1,2 Warfarin is prescribed mostly to prevent the progression or recurrence of acute deep vein thrombosis or pulmonary embolism as a second option after heparin. It is also used to prevent venous thromboembolism during surgery, such as orthopaedic or gynaecological surgeries, and as a prophylactic treatment in patients with chronic atrial fibrillation, acute myocardial infarction, a prosthetic heart valve or stroke.3 The basic mechanism of action of warfarin is inhibition of the activation of vitamin K-dependent clotting factors through the inhibition of vitamin K epoxide reductase (VKOR) enzyme, thus impairing the vitamin K cycle.4,5 The major limitation of warfarin is its low therapeutic index, and therefore it should always be given under strict safety controls.6,7 Higher doses of warfarin can cause bleeding while lower or subtherapeutic doses may lead to therapy failure.6,7 There are numerous reports on the variable responses by humans to fixed doses of warfarin.8 In addition, warfarin is the drug most often responsible for medication-associated death and is the second leading cause of drug emergency admissions in the USA.7,9 Therefore, the identification of the appropriate dose at the initiation stage of therapy is of paramount importance to minimize or even avoid these complications.9,10

The effect of warfarin therapy on the coagulation profile of an individual is measured by the international normalized ratio (INR), which is a universal conversion of the prothrombin time test.11 The prothrombin time (PT) test is used for monitoring and evaluating the effect of warfarin therapies and is a reliable measure of extrinsic pathways of coagulation.6,12

Variation in the VKOR complex 1 (VKORC1) gene accounts for up to 30% of the interindividual variation in maintenance doses.13,14 Other factors include age, weight, level of organ function, comedications, the disease itself, concomitant diseases, cultural and racial factors (including genetics), smoking, alcohol consumption and dietary preferences.15 Pharmacogenetics research in this area led to recommendations by the Food and Drug Administration (FDA) regarding variation in drug response according to genotypes.16 The genetic basis of variability among patients receiving warfarin was investigated by many researchers and single nucleotide polymorphisms (SNPs) in the non-coding region of the VKORC1 gene have been found to be suitable predictors of warfarin dosage requirements.1720 Warfarin sensitivity in patients treated with lower doses is frequently associated with the promoter region alternatives at SNP rs9923231. On the other hand, VKORC1 variant rs7294 is reported to be associated with warfarin resistance in patients who need higher doses than those with the wild-type variant.21 Although many SNPs have been reported in the VKORC1 gene, the FDA has recommended genetic testing for the rs9923231 SNP (A allele carriers) and for the CYP2C9 gene haplotypes.16 It has been demonstrated that warfarin-related genotyping can actually reduce treatment costs in high-risk patients.22 There have been a limited number of clinical research studies on warfarin usage in the United Arab Emirates (UAE), and no pharmacogenomics or pharmacogenetics studies. Therefore, the aim of this study was to determine the allele and genotype frequencies among Emiratis for the two most clinically relevant SNPs (rs9923231 and rs7294) in VKORC1 and compare them with other populations.

Materials and methods


Blood samples were collected from 117 healthy Emirati subjects from Al Ain and Abu Dhabi, UAE. All the individuals read the information sheet and signed informed consent forms to participate in the study. This study protocol was approved by the Ethics Committee for Human Research in the Al Ain District (CRD 261-Protocol No 13/38). Approximately 10 ml of peripheral venous blood was collected, 5 ml of which was placed in ethylenediaminetetraacetic acid-containing tubes to be genotyped. DNA was extracted from peripheral leucocytes using a whole-blood Qiagen extraction kit (FlexiGene DNA isolation kit, Qiagen, Hilden, Germany). The isolated genomic DNA samples were kept in sterile plastic vials at 4°C until analysis or stored at −20°C.

DNA sequencing and genotyping

Genotyping of the relevant SNPs was carried out using polymerase chain reaction (PCR) followed by Sanger sequencing. Primers for amplifying the relevant segments of the VKORC1 gene were designed using Primer3web, version 4.0.023,24 (, and were custom made by Metabion Inc. (Metabion International AG, Steinkirchen, Germany; Details of the primers used and PCR conditions are shown in Table 1.


Primers and PCR conditions used to amplify and sequence the two SNPs (rs9923231 and rs7294)

Primer name Annealing temperature (°C) Annealing time (s) Product size (bp)
58 60 290
60 45 659

[i] F, forward primer; R, reverse primer.

The two VKORC1-specific products (amplicons) from each subject were separated and analysed on 0.6% agarose electrophoresis gels to ensure a good PCR product quality prior to sequencing. The expected product size for the two SNPs was observed for all the analysed samples, as illustrated in Figure 1.


PCR products of the two SNPs on 0.6% agarose showing the expected product sizes.


DNA within the two amplicons was sequenced using the BigDye Terminator kit v3.1with a 3130xl Genetic Analyzer System (Applied Biosystems, Inc., Foster City, CA, USA) following ExoSAP-IT® (USB Corporation, Cleveland, OH, USA) treatment of the PCR products. Cycle sequencing was performed under standard conditions recommended by the manufacturers (Applied Biosystems, Inc.). The sequence at each SNP site was inspected carefully for each sample and recorded.

Statistical analysis

GraphPad Prism 5 (GraphPad Software, Inc., La Jolla, CA, USA) was used to apply selected statistical analysis. A chi-squared test for non-parametric variables was used to compare frequency results.


The frequencies of the three genotypes of the VKORC1 rs9923231 SNP (G3673A, or –1639 G > A, as it is commonly called in the literature), GG, GA and AA, and of alleles G and A are presented in Figure 2A and B, respectively. The frequencies of genotypes GG and AA are similar (0.256 and 0.248, respectively) while the frequency of the heterozygous genotype, GA, is 0.496. The frequency of the G allele is 0.504 and of the A allele is 0.496 (Table 2). In addition, we compared the results from this study with data from other populations, as shown in Figure 2A and B, and in Table 3. We used a chi-squared test to compare the differences in the allele frequencies among different populations. The results are shown in Figure 2B and Table 2; P < 0.05 was considered statistically significant. Statistical analyses were performed using GraphPad. The allele distribution in the UAE Emirati population was significantly different from that of the Chinese population (P < 0.001) and in the UAE population was significantly different from that of the Indian population (P < 0.001). There were no other significant differences in allele or genotype frequencies between other examined populations, such as Caucasians, Saudis and Iranians.


(A) Genotype frequencies of rs9923231 among Emiratis in comparison with other populations. (B) Alleles frequencies of rs9923231 among Emiratis in comparison with other populations. n, study sample size. Emirati population, n = 117; Saudi population, n = 131; Omani population, n = 356; Egyptian population, n = 207; Sudanese population, n = 203; Moroccan population, n = 114; Lebanese population, n = 568; Turkish population, n = 305; Iranian population, n = 126; Caucasian population, n = 22; Indian population, n = 43; Chinese population, n = 178. Source: Data for Emirati population from current study, Saudi population from Alzahrani et al.,25 Omani population from Pathare et al.,26 Egyptian population from Shahin et al.,27 Sudanese population from Shrif et al.,28 Moroccan population from Smires et al.,29 Lebanese population from Esmerian et al.30 and Djaffar-Jureidini et al.,31 Turkish population from Ozer et al.32 and Oner Ozgon et al.,33 Iranian population from Azarpira et al.,34 Caucasian population from NCBI,35 Indian population from Lee et al.,36 Chinese population from Miao et al.37

Table 2

Genotypes and alleles frequencies of rs9923231 among Emiratis

n = 117 (frequency)
Genotypes G/G 30 (0.256)
G/A 58 (0.496)
A/A 29 (0.248)
Alleles G 118 (0.504)
A 116 (0.496)

n, total number of study samples.

Table 3

Ethnic distribution of rs9923231 genotypes and alleles in various populations

UAE Saudi (Alzahrani et al.25) Omani (Pathare et al.26) Egyptian (Shahin et al.27) Sudanese (Shrif et al.28) Moroccan (Smires et al.29) Lebanese (Esmerian et al.30 and Djaffar-Jureidini et al.31) Turkish (Ozer et al.32 and Oner Ozgon et al.33) Iranian (Azarpira et al.34) Caucasian (NCBI35) Indian (Lee et al.36) Chinese (Miao et al.37)
Genotypes GG 0.256 0.374 0.415 0.255 0.411 0.404 0.248 0.311 0.16 0.318 0.838 0.006
GA 0.496 0.397 0.441 0.566 0.443 0.421 0.436 0.439 0.571 0.5 0.095 0.157
AA 0.248 0.229 0.145 0.178 0.144 0.175 0.315 0.249 0.27 0.182 0.068 0.837
Alleles G 0.504 0.573 0.637 0.538 0.633 0.614 0.467 0.531 0.444 0.569 0.884 0.084
A 0.496 0.427 0.363 0.462 0.367 0.386 0.533 0.469 0.556 0.431 0.116 0.916

The genotype frequencies of rs7294 among the 117 Emiratis recruited are shown in Figure 3A. The frequencies of the homozygous GG and AA genotypes were quite different, 0.462 and 0.145, respectively (Table 4). However, the frequency of the heterozygous GA is similar to that of the homozygous genotype (0.393). Allele frequencies are shown in Figure 3B: the frequency of the G allele is 0.660 and of the A allele is 0.340. Results from this study were compared with data in the literature from other populations, as shown in Figure 3A and B and Table 4. Unfortunately, it was not possible to find out genotype frequencies for either Iranian or Saudi populations as published papers did not clearly show the genotypes and alleles frequencies for rs7294.


(A) Genotype frequencies of rs7294 among Emiratis in comparison with other populations. (B) Allele frequencies of rs7294 among Emiratis in comparison with other populations. n, study sample size. Emirati population, n = 117; Sudanese population, n = 203; Caucasian population, n = 23; Indian population, n = 43; Chinese population, n = 551. Source: Data for Emirati population from current study. Data for Sudanese population from Shrif et al.,28 Caucasian population from NCBI,35 Indian population from Lee et al.,36 Chinese population from Chen et al.38

Table 4

Ethnic distribution of the rs7294 genotypes and alleles frequencies

n = 117
n = 150
(Shrif et al.28)
n = 23
n = 43
(Lee et al.36)
n = 551
(Chen et al.38)
Genotypes GG 0.462 0.43 0.435 0.081 0.813
GA 0.393 0.41 0.478 0.189 0.183
AA 0.145 0.16 0.087 0.730 0.004
Alleles G 0.660 0.637 0.674 0.186 0.905
A 0.340 0.363 0.326 0.814 0.095

n, total number of study samples.

Table 5

Genotype and allele frequency for rs7294 among Emiratis

n = 117 (frequency)
Genotypes GG 54 (0.462)
GA 46 (0.393)
AA 17 (0.145)
Alleles G 154 (0.660)
A 80 (0.340)

n, total number of study samples.

We used a chi-squared test (non-parametric test for discrete variables) to compare allele frequencies in different population (Table 4). There was a significant difference between the UAE Emirati population, and the Indian and Han Chinese populations (P < 0.001 in both cases). There were no significant differences in allele frequencies between the UAE Emirati population and Caucasian populations.

Allele and genotype frequencies for SNPs rs9923231 and rs7294 in the VKORC1 gene were found to be in Hardy–Weinberg equilibrium among the study sample of 117 UAE nationals.


This is the first pharmacogenetic study among Emiratis regarding VKORC1 allele and genotype frequencies. It has been suggested that 6–37% of the variation in warfarin dosage among individuals is due to SNPs in the VKORC1 gene.16,18,19 It is well documented that VKORC1 polymorphisms greatly influence warfarin dosage, and in some cases variation at the A allele may cause resistance, in the case of rs7294 variants, or sensitivity, in the case of the rs9923231 variant.18,19 Generally, there is a focus on the rs9923231 variant, which is located at the second nucleotide of an E-box (CANNTG) of the 5′ untranslated region (5′ UTR) of the VKORC1 gene.18 This variant plays a key role in the activity of the promoter region of the VKORC1 gene and it is believed to be a causative SNP for the low-dose warfarin requirement phenotype found in some patients.39 The enzyme activity of the G allele is higher than the A allele in this position.39 Polymorphism in rs9923231 interferes with mRNA expression in liver samples, as the A allele disturbs the binding of transcription factors to the VKORC1 gene promoter region, leading to a decrease in active mature copies of the VKORC1 protein.14 It is worth mentioning that the rs9923231 variant is the only SNP mentioned in FDA recommendations for warfarin leaflets amongst all the other important SNPs in the VKORC1 gene.16 However, many studies have shown the importance of other non-coding SNPs in VKORC1. These SNPs are mostly in perfect linkage disequilibrium with rs9923231.21 Based on several studies, the FDA has recommended genetic testing of warfarin for the VKORC1, rs9923231, A allele carriers and for the CYP2C9 gene haplotypes.40 According to the literature, patients with the G allele require a daily dose of 5 mg/day compared with 3.5–3.7 mg/day for patients with the A allele.5 Another study has reported that in patients with the A allele warfarin dose ranges from 2.9 to 3 mg/day, while in patients homozygous for the G allele it ranges from 5.5 to 6 mg/day.21 It has been postulated that rs9923231 is the best predictor of warfarin dose requirements, especially in the initial stages of warfarin therapy.21 The frequencies of the rs9923231 genotypes and alleles have been widely studied in different populations.39 This is useful in determining the appropriate dose based on ethnicity; for example, more than 90% of the Chinese population have the A allele and therefore patients of East Asian origin require lower doses of warfarin.39 The frequencies of the homozygous GG and AA genotypes of the rs9923231 variant in the total study sample are presented in Figure 2A and Table 2. We found that the frequencies of the GG and AA genotypes are similar [0.256 (30 subjects out of 117) and 0.248 (29 subjects out 117), respectively], while the frequency of the heterozygous GA genotype, which is a common genotype in the UAE population at this particular locus, is higher, at 0.496 (58 subjects out 117). This finding shows the difference in genotype distributions between UAE and Chinese populations, as 0.837 of the Chinese population exhibit a AA genotype, as shown in Figure 2A and Table 3. The higher frequency of the AA genotype among the Chinese population may explain the relatively low dose of warfarin required.3638 The GG genotype frequency in the Indian population is similar to that of the Chinese population, at 0.838, while the GG genotype frequency in the UAE population is similar found in Saudis, Iranians, Caucasians and other populations, as shown in Figure 2A and Table 3.2537 Our study shows that the two alleles are equally distributed among UAE nationals (frequency of 0.504 for the G allele and 0.496 for the A allele), as shown in Figure 2B and Table 3. Accordingly, Figure 2A shows that the frequencies of the G and A alleles of rs9923231 in the UAE population are similar to those seen in Saudis, and those from other Arab countries, and to those of the Turkish, Iranian and Caucasian populations, but differ significantly from the frequencies in Chinese and Indian populations. However, there is a slight difference between Omani and Sudanese populations (Figure 2A), as much previous research shows variability in genotype distribution even among neighbouring countries.

The second studied SNP, rs7294, or, as it called in the literature G9041A, or 3730 G > A, is located in the 3′ UTR of VKORC1. It is not correlated with any other SNPs in the VKORC1 gene.18 In general, this SNP is not found with the same haplotypes as rs9923231, which is the reason it was selected for our study. Genotyping of this SNP is not recommended by the FDA even though it is reported to be associated with warfarin resistance.22

Patients with the rs7294 allele variant need a high mean dose of approximately 40 mg/week.5 Patient homozygous for the A allele (AA) may require higher doses of warfarin than patients who are heterozygous (GA) or homozygous (GG) for the G allele.14

The allele and genotype frequencies of the rs7294 variant in the total study sample (117 subjects) are shown in Figure 3A and B and Tables 4 and 5. These data indicate some differences in the genotype frequencies: GG, 0.462 (54 out 117 subjects); AA, 0.145 (17 out 117 subjects); and GA, 0.393 (46 out 117 subjects). We found that the frequency of the G allele (0.660) was higher than of the A allele (0.340) (Figure 3B). When these genotype and allele frequencies were compared in different ethnic groups, those of the UAE population varied significantly from those in Indian and Chinese populations. The majority of the Indian population carry the A allele (0.814), which is associated with warfarin resistance, necessitating higher doses of warfarin, whereas more than 90% of the Chinese population carry the G allele, which is associated with the need for lower doses of warfarin. Distribution of rs7294 genotypes is similar in the Caucasian, Sudanese and Emirati populations.28,35

To reiterate, different ethnic groups require different doses of warfarin. For instance, the Chinese, in general, require lower doses than African Americans.3841 We found a variable distribution of genotypes for both SNPs, and, as a result, differences in warfarin requirements, among Emirati populations. In the case of other populations, such as the Chinese and Indians, knowledge of genetics can help predict the required dose and therefore it is important to determine the allele and genotype frequencies of important biomarkers that affect drug response.42,43 It is well known that the allele and genotype frequencies of many polymorphisms that influence drug response, sometimes dramatically, vary widely among racial or ethnic groups.44

Pharmacogenetics aims not only to identify variant alleles and genotypes that affect individual patients’ response to medication but also to guide and predict drug response depending on race/ethnicity.44,45 However, information on allele and genotype frequencies of important biomarkers involved in the pharmacogenetics and pharmacogenomics of frequently used medication by the Emirati population is limited. Pharmacogenetics research in the UAE started in 1996, earlier than in other countries, with the first research aimed at characterizing erythrocyte glucose-6-phosphate dehydrogenase deficiency among the UAE population.46 One year later, another genotype study investigated the allele frequencies of the NAT2 gene.47 Other pharmacogenetic studies in the UAE have reported several novel alleles and determined the alleles of CYP2D6.48

In conclusion, our data indicate that pharmacogenetic testing of rs9923231 and rs7294 variants might be relevant to the determination of warfarin dosage among the Emirati population. Implementation of genetic testing, at least for these two variants, is likely to have a direct effect with potential benefits to patients and the health care system in the UAE. This is also likely to have a direct impact on patient safety and reduce suffering and cost. We also report the frequencies of alleles and genotypes of these SNPs allowing us to compare them with other populations, which might be useful for genetic epidemiological studies.



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