Abstract Introduction Genotypic variations in the VKORC1

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The rs9923231 polymorphism in the
vitamin K epoxide reductase (VKORC1) gene is the single best predictor
of warfarin dose. However, replication studies on the correlation of the rs9923231
genotypes with anti-coagulant dose are sparse in the South
Indian population.

& Methods: A
cohort of 222 warfarin-treated patients was genotyped using
restriction fragment length polymorphism method.
The effect of the VKORC1 (-1639G>A) rs9923231 polymorphism on the variations
in the mean daily dose among genotypes were compared using one-way ANOVA and
linear regression analysis. The discriminatory ability of the rs9923231
polymorphism to bin the patients into high, intermediate or low dose categories
was assessed by estimating the proportional odds ratios using the ordered logit
regression analysis.

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Results: The frequency of the AA genotype and
A allele in the study sample was found to be 1.8% and 9.23%, respectively,
which was significantly different from the North Indian population. The mean daily
dose required to achieve the optimum international normalized ratio (INR) was
significantly lower in AA homozygous genotype carriers (3.99±1.67mg/day) and GA
heterozygous (4.26±1.57mg/day) compared to the GG genotype carriers
(5.61±2.41mg/day), p-value=0.004. The A allele carriers had a higher
odds of being grouped as a low dose requiring category (adjusted OR 3.31, 95%
CI 1.52 – 7.21, p-value=0.003), compared to non-carriers.

These preliminary results strongly support
the use of the VKORC1 (-1639G>A)
rs9923231 polymorphism for genetically guided
initial warfarin dosing in South Indian patients with heart valve replacements.




Keywords: VKORC1, polymorphism, warfarin, pharmacogenetics,





































Genotypic variations in the VKORC1 gene contribute significantly
to warfarin sensitivity among patients 1, 2. Inherent differences in allele
frequencies have revealed varying dose requirements for warfarin across
populations 3.  Various studies have reported significant geographic
differentiation in the observed allele frequencies for the VKORC1 and CYP2C9
gene polymorphisms from Asian populations 4. Distinct Indian
subpopulations have also shown a great degree of pharmacogenetic variations in
the VKORC1, CYP2C9 and CYP4F2 genes 5. In this context,
subpopulation-specific replication studies designed to capture the genotypic
distribution of pharmacogenetic variants are essential to assist clinicians in
optimizing dose regimes. Moreover, incorporating the ethnic background of the
patient as an additional variable can significantly improve the predictability
of anticoagulant dosing algorithms 6.

The polymorphisms in the VKORC1
gene explains up to 25-50% of the variance in anti-coagulant dose 7-10. The
strong association between haplotypes of the VKORC1 gene polymorphisms and warfarin dose phenotypes
are distinguished by the tag-SNP rs9923231 present in the
promoter of the gene. At the transcriptional level, the A allele of the
rs9923231 SNP has been found to be associated with a 70% reduction of VKORC1
mRNA levels compared to the G allele, by abolishing an E-box consensus sequence in the promoter region 11,
12. A few studies from South India have
published data regarding the VKORC1 (-1639G>A) rs9923231
polymorphism and its effect on daily warfarin dose requirement 13-18.
Meanwhile, other studies on South Indian populations restricted their findings
to report allele and genotypic frequencies without accessing association with
dosage requirements 5, 19, 20. Comparative studies on North Indian
populations have reported conflicting allele and genotype frequencies possibly
due to reduced sample sizes 19, 21, 22. At present, there are no reports on
the VKORC1 (-1639G>A) rs9923231
polymorphism and its association with warfarin dose requirements exclusively
from Kerala, the southernmost state of India with a predominant Dravidian
population. Therefore, the aims of this study were to determine the frequency
of the VKORC1 (-1639G>A)
rs9923231 polymorphism in the South Indian population of Kerala, to assess
variation of mean daily dose among carriers of the three genotypes and to
determine its ability to discriminate patients belonging to high, intermediate
and low dose categories.


Materials and Methods


Patient Sample

A total of 222 patients having a stable therapeutic INR were recruited
from the INR clinic of the Cardiology Department, Sree Chitra Tirunal Institute
for Medical Sciences and Technology (SCTIMST), Trivandrum, Kerala. Stable
therapeutic INR was defined as having at least two consecutive INR measurements
between 2.5 and 3.5 on the same anti-coagulant dose measured at least one week
apart. Patients over
the age of 18 years who needed anticoagulation with warfarin or acenocoumarol after
prosthetic mitral valve replacement with tilting disc valve for rheumatic heart
disease and having normal prosthetic valve function were included in this
study. Patients with renal dysfunction, hepatic dysfunction, and patients on
other anti-coagulants such as Dindevan (Phenindione) were excluded from the
study. All participants belonged to the
Malayalam speaking South Indian population of Kerala. The study was
approved by the Institutional Ethics Committee of the SCTIMST and conformed to
the guidelines set by the Declaration of Helsinki.



DNA isolation and PCR-RFLP

Genomic DNA was isolated from
three milliliters of whole blood samples taken from patients after obtaining
written informed consent, using the modified Rapid-Method 23. A
PCR-restriction fragment length polymorphism method (RFLP) was designed to
identify the VKORC1 -1639G>A
(rs9923231) SNP. A 15 ?l PCR reaction mixture
was prepared to amplify 100 ng gDNA mixed with 1 ?l 10× Taq buffer, 200 ?M
dNTPs (Invitrogen), 250 ?M MgCl2, 0.5U Taq Polymerase (NEB) and 10
?M of each forward and reverse primers. PCR cycling conditions consisted of an
initial denaturation for 2 min at 95 °C; followed by 35 cycles of denaturation
at 95 °C for 30 s, annealing at 60 °C for 45 s and extension at 72 °C for 45 s,
with a 10 min final extension at 72 °C, done using Biorad MJ MiniTM
thermal cycler. Human-specific primers were VKORC1-F,
designed using the Primer Premier v.5 software.

The 496 bp PCR product
was digested with NciI restriction enzyme, according to manufacturer’s
protocol (NEB, Inc., USA). Products were separated on 2.5 % agarose gel
alongside a 100bp DNA ladder, and stained with ethidium bromide for
visualization (Fig. 1). Scoring of the AA homozygous genotype was done
by observing the presence of a single uncut band of size 496 base pairs (bp). The
GG homozygous genotype was scored by two bands of 392 and 104 bp, and the GA
heterozygous genotype by the presence of three bands of sizes 496, 392 and 104
bp. Approximately 10% of the samples were reanalysed to ascertain 100%
concordance in genotyping. The genotypes inferred from the NciI
digestion patterns were further confirmed by direct sequencing using ABI PRISM
3730 Genetic Analyser (Applied Biosystems), as shown in Fig. 2. The
sequence traces were queried for sequence similarity using the BLAST tool (http://blast.ncbi.nlm.nih.gov/Blast.cgi).


Statistical analysis

Deviation of allelic frequencies from Hardy-Weinberg
equilibrium was examined using the Pearson’s chi-square test implemented in the
FINETTI program (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl). The mean INR-based daily dosage of anti-coagulant required
by the genotypes of the VKORC1 (-1639G>A) polymorphism was estimated
using a linear regression analysis. Three models were analysed, the first
unadjusted model had only the genotype variables, the second model was adjusted
for age, sex, and BMI and the third model included amiodarone in addition to
age, sex and BMI. Negative regression coefficients corresponded to the reduced
amount of warfarin dose required in the presence of the variant genotypes
compared to the GG genotype used as the reference. The genotype-based daily doses were predicted using the
regression coefficient from the third regression model. Student’s t-test was
used to compare means of the INR-based and genotype-based daily doses. The
variation in mean daily dose among patients carrying the three different
genotypes GG, GA and AA of the VKORC1 (-1639G>A) rs9923231 polymorphism were
compared using one-way ANOVA test.


logit regression analysis was used to evaluate the predictive value of VKORC1 (-1639G>A) rs9923231
polymorphism in dose categorization of the patients. To measure the predictive
ability of the genotypes to segregate the study cohort into any of the three
dose categories, the therapeutic dose estimates were categorized as high-dose
(?49 mg per week), intermediate dose (>21 and <49 mg per week), and low-dose (?21 mg per week) groups. This was in accordance with the International Warfarin Pharmacogenetics Consortium, 2009, and recoded as 1, 2 and 3, respectively 1. Three models were used to calculate (1) the unadjusted odds; (2) the odds ratios adjusted for age, sex and BMI; and (3) the odds ratios adjusted for age, sex, BMI, and amiodarone. All analyses were performed using statistical software STATA version 13.0 (Stata Corp, TX). P-value <0.05 was considered statistically significant.     Results The study group comprised of 112 females (50.4%) with a mean age of 48.3±10.8 years and 110 males (49.6%) and with mean age of 48.8±12.6 years. Twenty-one patients had adverse events like bleeding (9.5%) during the follow-up period. Atrial fibrillation was present in 99 patients (44.6%). Other risk factors included smoking (9%), systemic hypertension (3.6%), dyslipidemia (7.2%) and diabetes mellitus (3.2%). Concomitant medications included digoxin (34.7%), aspirin (16.7%), clopidogrel (2.7%), and amiodarone (4.1%).   The frequency of the GG, GA and AA genotypes of VKORC1 (-1639G>A) rs9923231
polymorphism among the 222 patients
were 83.33%, 14.86% and 1.8%, respectively (Table 1). The allele frequency of
the G allele was 90.77% and that of the A allele was 9.23%, with no significant
deviation from Hardy-Weinberg equilibrium (p-value=0.10).
The association of the VKORC1 (-1639G>A) genotypes with the required
INR-based daily dose is shown in Table 2. The GA genotype and the combined
GA+AA genotypes (dominant model), required significantly lower dose compared to
the GG genotype (1.35 mg/day and 1.38 mg/day less, respectively).

Among the three genotypes the mean INR-based and
genotype-based daily dose were significantly different, p-value=0.0044 and <0.0001, respectively (Table 3). The GG genotype carriers required an INR-based daily dose of 5.61mg/day compared to the GA and AA carriers who required a daily dose of 4.26 and 3.99 mg/day, respectively. The mean of the INR-based daily dose was similar to the predicted genotype-based daily dose with 5.38± 2.34 mg/day and 5.38± 0.66 mg/day, respectively (p-value=0.50)   Table 4. shows the proportional odds ratios and 95% confidence intervals (CI) of the ordered logit regression analyses. Each model shows the proportional odds ratio of a patient carrying a variant genotype, either GA or AA, or grouped as GA+AA (dominant model), of being in a low dose category versus the combined intermediate and high dose. For GA genotype carriers in model 1, the unadjusted odds of being in the low warfarin dose category versus the intermediate and high dose categories were 3.18 times higher than for GG genotype carries (reference) (p-value=0.004). Likewise, for the AA genotype carriers being in the low dose category versus the /intermediate and high warfarin dose categories were 9.66 times higher than for GG genotype carries (p-value=0.023). When GA and AA genotypes are grouped as in a dominant model, the unadjusted odds of them being in the low versus the combined intermediate and high dose category was 3.6 times higher compared to GG genotype carriers (p-value=0.001). This trend continued even after controlling for the effects of age, sex, BMI and amiodarone usage in models 2 and 3 (p-value<0.05).     Discussion The VKORC1 gene is considered the most important individual predictor of warfarin dose 24-26. Initially, D'Andrea et al. had identified the VKORC1 (1173C>T) rs9934438 polymorphism in
intron 1 to correlate with higher warfarin dose requirement 27. A subsequent
study in Asian patients by Yuan et al. found the VKORC1 (-1639G>A)
rs9923231 promoter polymorphism as a novel candidate, which was replicated
simultaneously by other studies that included additional SNPs or by complete
mapping of all SNPs in the VKORC1 gene 7, 11, 28. In a later study by
Wadelius et al., 29 genes in the warfarin pharmacological pathway were tested
for association using approximately 900 SNPs in 201 patients of North European
descent 8. They found the VKORC1 as the single gene most strongly
associated with warfarin dose. Further high-density mapping of the VKORC1
region on chromosome 16 revealed that three SNPs (rs2359612, rs9934438 and
rs9923231) were in strong linkage disequilibrium (LD) and accounted for
approximately 30% of the warfarin dose variance.

the unusual allele frequency distribution observed worldwide, the VKORC1
gene along with CYP2C9 has been found to consistently affect warfarin
dose across populations. The extensive geographic differentiation of
rs9923231 SNP is notable in that the A allele is almost absent in African
populations, whereas it shows extremely high frequencies in East Asian
populations, indicative of positive selection among East Asians 24. The
high level of geographic differentiation along with significant effect on
warfarin drug dosing makes it an important gene to be studied in detail.
Unfortunately, it has been poorly characterized in the subpopulations of the
Indian subcontinent.

present study estimated the minor A allele frequency (MAF) of the rs9923231 SNP
at 9.23% in a South Indian population from Kerala. Other significant findings
revealed a distinct variation of mean daily dose among the GG, GA and AA
genotype carriers. The genotype predicted daily dosage calculated from the
regression model was found to be very similar to the INR-based daily dosage,
indicating the predictive value of VKORC1 (-1639G>A) rs9923231
genotyping for clinical use. The presence of the A allele (associated with
low-dose) when present either as heterozygous or homozygous genotypes showed a statistically
significant capacity to discriminate patients belonging to high, intermediate
and low dose categories. Since the present work was designed as a pilot study,
the effects of variants in the CYP2C9 and CYP4F2 genes were not studied and may be
perceived as a limitation of the study. Future studies that would
include the CYP2C9 and CYP4F2 genes, and additional environmental
risk factors, conducted with larger sample sizes could provide a more
accurate model to predict individual dose requirement.

is also worth mentioning that Rathore et al.  found distinct frequencies of CYP4F2 1347
G>A and GGCX 12970 C>G polymorphisms in 225 North Indian patients
(MAF; 43.6% and 0.03%, respectively). They reported that these polymorphisms
did not have a significant bearing on the maintenance dose of acenocoumarol
oral anticoagulant in cardiac valve replacement patients 29. On the contrary,
Krishna Kumar et al. reported that the CYP4F2 rs2108622 and GGCX
rs11676382 polymorphisms were important predictive factors of warfarin for 240
patients of South Indian ethnicity (MAF; 34.2% and 1.0%, respectively) 15.
This indicates that fundamental differences in allele and haplotype frequencies
leading to distinct differences in linkage disequilibrium patterns in Indian
subpopulations may explain variability in warfarin dose requirements. Kumar et
al. have exemplified this by studying the haplotype structure and pair?wise LD pattern of the eight VKORC1 SNPs identified
in the Tamil South Indian population. A strong LD pattern (D’>0.8) was
observed between seven out of eight SNPs which included VKORC1
(-1639G>A) rs9923231 in the promoter region and VKORC1 (1173C>T)
rs9934438 in intron 1 30. Hence, identifying genetic polymorphisms that are
predominant or exclusive to Indian subpopulations through resequencing and
construction of LD maps could significantly increase the proportion of
variability that can be explained for warfarin dose requirements.

genetic polymorphisms will help in predicting the average dose requirement in
patients after a valve replacement. This will help in reducing the time to titration
to the target dose and also may reduce the hospital stay and also the number of
INR checks required to attain the target dose. This reduces costs and is
important in a developing country like India where accessibility to INR
checking facilities and also affordability is a major issue. 


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