The effect of CYP2C9, VKORC1 and CYP4F2 polymorphismand of clinical factors on warfarin dosage during initiationand long-term treatment after heart valve surgery

Vacis Tatarunas • Vaiva Lesauskaite • Audrone Veikutiene •

Pranas Grybauskas • Povilas Jakuska • Laima Jankauskiene •

Ruta Bartuseviciute • Rimantas Benetis

� Springer Science+Business Media New York 2013

Abstract The dosage of warfarin is restricted due to its

narrow therapeutic index, so, the required dose must be

adapted individually to each patient. Variations in warfarin

dosage are influenced by genetic factors, the changes in

patient diet, anthropometric and clinical parameters. To

determine whether VKORC1 G3730A and CYP4F2

G1347A genotypes contribute to warfarin dosage in

patients during initiation and long-term anticoagulation

treatment after heart valve surgery. From totally 307

patients, who underwent heart valve surgery, 189 patients

(62 %) who had been treated with warfarin more than

3 months, were included into the study. A hierarchical

stepwise multivariate linear regression model showed, that

during initiation clinical factors can explain 17 % of the

warfarin dose variation. The addition of CYP2C9 and

VKORC1 G-1639A genotype raises the accuracy about

twice—to 32 %. The CYP4F2 G1347A genotype can add

again about 2–34 %. During long-term treatment clinical

factors explain about 26 % of warfarin dose variation. If

the CYP2C9 *2, *3, VKORC1*2 alleles are detected, model

can explain about 49 % in dose variation. The *3 allele of

VKORC1 raises the accuracy by 1–50 %. The carriers of

CYP4F2 A1347A genotype required higher daily warfarin

doses during initiation of warfarin therapy after heart valve

surgery than comparing to G/G and G/A carriers, but

during the longer periods of warfarin use, the dosage of

warfarin depended significantly on VKORC1 *3 allele

(G3730A polymorphism) and on the thyroid stimulating

hormone level in the blood plasma.

Keywords CYP4F2 � VKORC1 � Anticoagulation

treatment � Warfarin

Introduction

Warfarin is one of the most popular anticoagulants

worldwide, which is used for long-term management and

prevention of thromboembolic complications. Despite that

it has been in use more than 50 years, until now it remains

one of the most efficient anticoagulant even in comparison

with the new generation anticoagulants. Its main disad-

vantage is as it has a narrow therapeutic index, making the

anticoagulant therapy complicated [1]. The required sta-

bilization dosage must be adapted individually to each

patient at initiation of anticoagulation therapy (so, inter-

national normalized ratio (INR) monitoring and dosage

adjustment must be made frequently) during the first

months of treatment, as well as, maintenance doses should

be correctly adjusted according to the changes in patient

diet, anthropometric and clinical parameters [2]. Reperfu-

sion during cardiopulmonary bypass (CPB), infections of

the wounds during post-surgical period—these factors can

have an indirect effect on warfarin dosage during initiation,

as they have a significant effect on severity of inflamma-

tory response: during inflammation coagulation is

V. Tatarunas (&) � V. Lesauskaite � A. Veikutiene �P. Grybauskas � P. Jakuska � L. Jankauskiene �R. Bartuseviciute � R. Benetis

Institute of Cardiology, Lithuanian University of Health

Sciences, Sukileliu 17, 50009 Kaunas, Lithuania

e-mail: vaciss@yahoo.fr

A. Veikutiene � P. Jakuska � R. Benetis

Department of Cardiac, Thoracic, and Vascular Surgery,

Lithuanian University of Health Sciences, Eiveniu 2,

50009 Kaunas, Lithuania

L. Jankauskiene

Department of Internal Diseases, Lithuanian University

of Health Sciences, Eiveniu 2, 50028 Kaunas, Lithuania

123

J Thromb Thrombolysis

DOI 10.1007/s11239-013-0940-x

activated, but the expression of different drug-metabolizing

enzymes decreases [3].

Warfarin metabolism depends on highly polymorphic

enzyme CYP2C9 of hepatic P 450 cytochrome. The variant

alleles *2 (rs1799853) and *3 (rs1057910) which encodes

hypofunctional enzyme, impairs the metabolism and

elimination of warfarin. The target of warfarin is an

enzyme called vitamin K epoxide reductase (VKORC1).

Thus, warfarin blocks the activity of VKORC1 and stops

the reduction of vitamin K epoxide, which is used to pro-

duce active clotting factors. In 2005 Rieder et al. [2] first

identified the main haplotype combinations of VKORC1,

affecting warfarin dosage. Later, it was found that, the

most common alleles in European and in Asian populations

having significant effect on warfarin doses are VKORC1 *2

and *3 alleles: G-1639A (rs9923231) and G3730A

(rs7294), respectively [2, 4, 5]. The *2nd allele was more

extensively studied in comparison to the *3rd allele. Dif-

ferent studies published during recent years confirm that

demographic, anthropometric and clinical factors in com-

bination with the *2, *3 alleles of CYP2C9 and of VKORC1

can be used as biomarkers to give useful indications in

adjustment of warfarin dosage by more than 60 % in

warfarin dose variation usually in Asian populations [5–9].

The *3 allele was found to have an impact during stable

dosage of warfarin [5]. However, still a half of warfarin

dosage variation remains unexplained by any existing

algorithm.

Recently CYP4F2 was identified as having an impact on

warfarin dosage [10]. Caldwell et al. [10] was first to

publish, that the dosage of warfarin correlated with

patients’ CYP4F2 G1347A (rs2108622) polymorphism

during stable period of dosage, as CYP4F2 synthesizes a

20-Hydroxyeicosatetraenoic acid (20-HETE), CYP4F2 can

also metabolize vitamin K1 into inactive form and play a

significant effect on daily dosage of warfarin [11]. Very

recently Bejarano-Achache et al. [12] detected a measur-

able effect of CYP4F2 on warfarin dose during induction

of the treatment, but the difference was not of statistical

significance.

The objective of this work was to determine whether

VKORC1 G3730A and CYP4F2 G1347A genotypes con-

tribute to warfarin dosage in patients during initiation and

long-term anticoagulation treatment after heart valve

surgery.

Population description

From totally 307 patients, who underwent heart valve

surgery at the Department of Cardiac, Thoracic and Vas-

cular Surgery of Lithuanian University of Health Sciences

from February of 2009 to September of 2011, 189 patients

(62 %) who had been treated with warfarin more than

3 months and represented a sample of the patients with

mechanical heart valve replacement or the patients after

biological valve implantation with additional risk factors

such as atrial fibrillation, left ventricular failure, or history

of thromboembolism, were included into the study. The

sample consisted of 118 (62.4 %) men and 71 (37.6 %)

women. Their age ranged from 27 till 87 years (median

68 years). After the heart valve surgery operation patients

were treated at the hospital from 8 till 84 days (median

17 days).

After heart valve surgery, patients were anticoagulated

by heparin and warfarin. A standard 5 mg loading dose of

warfarin was given to all of the studied patients so as to

achieve an INR at the target range of 2–3.5. When the

target INR had been reached, heparin was discontinued.

The end-point of INR assessment was considered at the

patient’s discharge from the Department of Cardiac, Tho-

racic and Vascular Surgery.

Baseline characteristics of the studied patients‘ sample

Patients‘ demographic (e.g., gender, age, height, weight)

and clinical characteristics were obtained from their case

histories. The main clinical factors are presented in

Table 1. Concomitant medication, which has been used

during initiation of warfarin therapy, is listed in Table 2.

Table 1 Clinical factors and the dosage of warfarin during induction

and during long-term treatment in mg

Variable During induction During long-term treatment

n Mean ± SD n Mean ± SD

Diabetes

Present 29 (15.3) 5.25 ± 2.10 29 (15.3) 4.53 ± 1.50

Absent 160 (84.7) 5.63 ± 2.91 160 (84.7) 5.09 ± 2.26

Free thyroxine concentration

Low – – 7 (3.7) 5.11 ± 1.31

Normal – – 179 (94.7) 5.00 ± 2.20

High – – 3 (1.6) 5.18 ± 2.94

High creatinine

Present 16 (8.5) 4.59 ± 2.84 28 (14.8) 4.14 ± 1.73

Absent 173 (91.5) 5.66 ± 2.79 161 (85.2) 5.16 ± 2.21

Thyroid stimulating hormone level

Lowa – – 18 (9.5) 5.32 ± 2.36

Normal – – 158 (83.6) 5.08 ± 2.19

Highb – – 13 (6.9) 3.74 ± 1.24

Thyroid hypofunction

Present 7 (3.7) 6.64 ± 1.65 – –

Absent 182 (96.3) 5.53 ± 2.83 – –

Total 189 (100.0) 5.57 ± 2.80 189 (100.0) 5.01 ± 2.17

a Low versus high—p = 0.03b Normal versus high—p = 0.03

V. Tatarunas et al.

123

Table 2 Concomitant

medication usage and daily

warfarin dosage in mg

Drug During initiation of warfarin therapy During long-term treatment

n % Mean ± SD n % Mean ± SD

ACE inhibitor

Users 115 60.8 5.41 ± 2.76 117 61.9 5.20 ± 2.07

Non-users 74 39.2 5.82 ± 2.87 72 38.1 4.70 ± 2.31

Acetaminophen

Users 123 65.1 5.51 ± 2.86 – – –

Non-users 66 34.9 5.69 ± 2.71 – – –

Angiotensin II receptor blockers

Users 16 8.5 6.25 ± 3.79 29 15.3 5.00 ± 1.89

Non-users 173 91.5 5.51 ± 2.70 160 84.7 5.01 ± 2.22

Ambroxol

Users 14 7.4 3.64 ± 1.75 – – –

Non-users 175 92.6 5.72 ± 2.82 – – –

Amiodarone

Users 67 35.4 4.67 ± 2.64 29 15.3 3.99 ± 2.11

Non-users 122 64.6 6.06 ± 2.78 160 84.7 5.19 ± 2.14

Aspirin

Users 14 7.4 5.12 ± 2.67 3 1.6 7.33 ± 3.21

Non-users 175 92.6 5.61 ± 2.82 186 98.4 4.97 ± 2.14

b-Blockers

Users 165 87.3 5.64 ± 2.74 163 86.2 5.04 ± 2.18

Non-users 24 12.7 5.09 ± 3.20 26 13.8 4.81 ± 2.13

Benzodiazepines

Users 114 60.3 5.59 ± 3.13 15 7.9 3.75 ± 1.29

Non-users 75 39.7 5.54 ± 2.23 174 92.1 5.12 ± 2.20

Calcium channel blocker

Users 6 3.2 5.50 ± 4.33 13 6.9 3.64 ± 1.37

Non-users 183 96.8 5.57 ± 2.76 176 93.1 5.11 ± 2.19

Cephalosporin

Users 41 21.7 6.08 ± 3.45 – – –

Non-users 148 78.3 5.43 ± 2.59 – – –

Diclophenac

Users 40 21.2 5.14 ± 2.81 – – –

Non-users 149 78.8 5.69 ± 2.80 – – –

Loop diuretic

Users 160 84.7 5.66 ± 2.62 100 52.9 4.59 ± 2.27

Non-users 29 15.3 5.06 ± 3.66 89 47.1 5.48 ± 1.96

Ibuprofen

Users 23 12.2 6.35 ± 3.43 – – –

Non-users 166 87.8 5.46 ± 2.70 – – –

Ivabradin

Users 17 9.0 6.70 ± 3.09 8 4.2 5.13 ± 1.69

Non-users 172 91.0 5.46 ± 2.76 181 95.8 5.00 ± 2.19

Ketorolac

Users 18 9.5 5.47 ± 2.86 – – –

Non-users 171 90.5 5.58 ± 2.80 – – –

Ketoprofen

Users 126 66.7 5.91 ± 2.83 – – –

Non-users 63 33.3 4.90 ± 2.64 – – –

The effect of CYP2C9, VKORC1 and CYP4F2 polymorphism

123

Collection of clinical data during long-term

anticoagulation

The patients who continued to use warfarin after heart

valve surgery more than 3 months (minimal period

90 days, maximal 711 days, median 274 days) were asked

to arrive again. Blood was taken for blood coagulation and

biochemical tests (Table 1). The cardiologist examined the

patient and collected the required data, such as: the dose of

warfarin, the use of concomitant medications (Table 2).

The results of biochemical parameters (blood coagulation

test (INR); the level of the blood alkaline phosphatase

(ALP), glutamic oxaloacetic transaminase (GOT), glutamic

pyruvate transaminase (GPT), thyroid-stimulating hormone

(TSH), free thyroxine (FT4) and the concentration of blood

creatinine) were assessed as well.

Materials and methods

DNA extraction and genotyping

Blood samples for DNA extraction were collected in 3 ml

tubes containing potassium EDTA. Total genomic DNA

was extracted from peripheral blood leukocytes by using

the salting-out method [13]. Five single nucleotide poly-

morphisms of interest: CYP2C9*2 (rs1799853), CYP2C9*3

(rs1057910), VKORC1 G-1639A (rs9923231), VKORC1

G3730A (rs7294) and CYP4F2 G1347A (rs2108622) from

each patient, were assessed by using commercial Taqman

probes (Applied Biosystems, UK) by using ABI 7900HT

fast real-time PCR Thermocycler (USA) in the laboratory

of Molecular Cardiology of the Institute of Cardiology of

Lithuanian University of Health Sciences. Real-Time

polymerase chain reaction was done in a final volume of

25 ll, containing 12.5 ll of 19 Universal PCR Master Mix

(Applied Biosystems, USA), 10.25 ll of PCR Grade water

(Ambion, USA), 1.25 ll of each Taqman probe and

10–30 ng of genomic DNA per reaction. Amplification was

done according to manufacturer’s protocol for validated

probes: 10 min at 95 �C, followed by 40 cycles: 15 s at

95 �C and 2 min at 60 �C).

Written informed consent was obtained from all patients

included in this study. Permission for this study was

obtained from Regional bioethics committee of Kaunas

(Lithuania) in 2007.12.04. The permission number is BE-2-

50.

Statistical analysis

Results are presented as mean ± SD if it is not mentioned

otherwise. A p B 0.05 was taken as statistically significant.

Frequency of genotypes and alleles in patient sample is

presented in % (percent). The relationship between the

warfarin dose used daily and patient demographic,

anthropometric, clinical and genetic data were established

by using multivariate linear regression analysis.

Results

Data on anticoagulation monitoring

During initiation of the therapy patients were treated with

5.57 ± 2.80 mg/day of warfarin, but during long-term

treatment they used less warfarin (5.01 ± 2.17 mg/day)

(Table 2). During the long-term treatment period, there

were less patients having the required therapeutic INR,

than at the time of the discharge from the hospital (65.6 vs

42.9 %, p = 0.001, respectively). During long term treat-

ment significantly increased number of under-anticoagu-

lated patients as compared to the induction phase of the

treatment (51.8 vs 17.5 %, p \ 0.001, respectively)

(Table 3).

The influence of demographic and anthropometric

factors

The dose of warfarin correlated with patients’ age and body

weight during initiation (r = -0.298, p \ 0.001 and

Table 2 continuedDrug During initiation of warfarin therapy During long-term treatment

n % Mean ± SD n % Mean ± SD

Spironolactone

Users 87 46.0 5.65 ± 3.05 47 24.9 4.73 ± 2.11

Non-users 102 54.0 5.50 ± 2.59 142 75.1 5.10 ± 2.19

Statin

Users 72 38.1 5.33 ± 2.72 47 24.9 4.96 ± 2.25

Non-users 116 61.4 5.70 ± 2.86 142 75.1 5.03 ± 2.15

Total 189 100.0 5.57 ± 2.80 189 100.0 5.01 ± 2.17

V. Tatarunas et al.

123

r = 0.174, p = 0.016, respectively), and long-term treat-

ment (r = -0.398, p \ 0.001 and r = 0.305, p \ 0.001,

respectively).

The influence of clinical factors on warfarin therapy

During long-term treatment, these patients, who had higher

level of serum creatinine (n = 28), required less warfarin

as compared to patients with normal serum creatinine level

(p \ 0.02). The patients, who had low level of TSH,

required significantly more warfarin than these, who had

normal or high TSH level. Other factors had no significant

impact on daily dosage of warfarin (Table 1).

During initiation of the therapy, concomitant use of

ambroxol, amiodarone and ketoprofen, significantly

reduced the required dosage of warfarin while other med-

ications had no impact on warfarin dose (Table 2). Of these

drugs, only amiodarone was continued during long-term

treatment. The users of amiodarone, benzodiazepines,

calcium channel blockers (CCB), torasemide required less

warfarin versus non-users. Other drugs had no significant

effect on warfarin dose.

The effect of CYP2C9, VKORC1 and CYP4F2 gene

polymorphism

CYP2C9*1*1 was detected in 69.3 % of the studied

patients. These patients required the highest dosages of

warfarin as well as during initiation (5.87 ± 2.94 mg/day),

as well as during long-time treatment (5.33 ± 1.99 mg/

day). The carriers of CYP2C9 variant *2 and *3 alleles

required less warfarin as it is presented in Table 4. The

lowest doses (even half-lower doses than for *1*1 geno-

type carriers) were given to *2*3 and *1*3 genotype car-

riers, who represented only 14.3 % of the studied patients’

sample.

Homozygous VKORC1 G-1639G patients (representing

39.7 % of the studied sample) were treated with higher

doses (as well as during initiation 6.62 ± 2.84 mg, as well

as during long-term treatment 5.85 ± 2.34 mg/day) than

heterozygous G/A. A half-less of warfarin doses as

compared to G/G carrying patients required A/A homo-

zygous patients, representing 14.8 % of the patients.

VKORC1 A3730A carriers (21.7 %) required higher

doses of warfarin compared to A/G and G/G genotype

carriers. As well as during induction, the highest doses of

warfarin used these patients, who had VKORC1 A3730A

genotype.

During initiation the carriers of CYP4F2 A1347A, rep-

resenting only 5.3 % of the studied sample, required more

warfarin, as compared to CYP4F2 G/A and G/G carriers.

During long-term treatment the dosage of warfarin did not

differ in CYP4F2 G/G G/A and A/A carriers.

The regression model of warfarin dosage

To establish the main factors which impacted the dosage of

warfarin, we have used a hierarchical stepwise multivariate

Table 3 A level of anticoagulation during induction and during long-term treatment

Variable During induction During long-term treatment

n % Mean SD n % Mean SD

INR \ 2 33 17.5 1.70 0.20 98 51.8 1.56 0.24

2 B INR B 3.5 124 65.6 2.69 0.38 81 42.9 2.42 0.33

INR [ 3.5 32 16.9 4.27 0.95 10 5.3 4.17 0.46

Total 189 100.0 2.78 0.91 189 100.0 2.06 0.71

Table 4 Warfarin daily dose during induction in mg in accord to

CYP2C9, VKORC1 and CYP4F2 genotype

Genotype n % During induction

warfarin

(mean ± SD)

During

long-term

treatment

warfarin

(mean ± SD)

CYP2C9 *1*1 131 69.3 5.87 ± 2.94 5.33 ± 1.99

CYP2C9 *1*2 28 14.8 5.52 ± 2.48 5.07 ± 2.74

CYP2C9 *1*3 23 12.2 4.25 ± 2.01 3.64 ± 1.77

CYP2C9 *2*2 3 1.6 5.16 ± 2.75 4.56 ± 1.91

CYP2C9 *2*3 4 2.1 3.87 ± 2.43 2.30 ± 1.40

VKORC1 G-1639G 75 39.7 6.62 ± 2.84 5.85 ± 2.34

VKORC1 G-1639A 86 45.5 5.38 ± 2.60 4.78 ± 1.91

VKORC1 A-1639A 28 14.8 3.35 ± 1.72 3.46 ± 1.33

VKORC1 A3730A 41 21.7 6.60 ± 2.67 6.23 ± 2.47

VKORC1 A3730G 70 37.0 5.51 ± 2.57 5.08 ± 1.82

VKORC1 G3730G 78 41.3 5.08 ± 2.95 4.30 ± 2.02

CYP4F2 A1347A 10 5.3 6.47 ± 4.11 4.93 ± 2.66

CYP4F2 G1347A 67 35.4 5.54 ± 2.82 5.18 ± 2.15

CYP4F2 G1347G 112 59.3 5.51 ± 2.67 4.92 ± 2.16

The effect of CYP2C9, VKORC1 and CYP4F2 polymorphism

123

linear regression model. Only these factors, which impac-

ted the dosage of warfarin significantly, were included into

regression model. INR value was introduced into both

models representing the dosage of warfarin: during initia-

tion and also, during long-term treatment.

During initiation patients’ clinical factors can explain

17 % of the warfarin dose variation. The detection of

CYP2C9 *2, *3 and VKORC1 *2 (G-1639A) alleles, raises

the accuracy about twice—to 32 %. The addition of

CYP4F2 G1347A adds about 2 % to the accuracy of this

model (Table 5).

The factors such as patients’ age, body weight, INR,

TSH activity, use of concomitant medication (amiodarone,

benzodiazepines and calcium channel blockers) can

explain about 26 % of warfarin dose variation during long-

term treatment. The presence of CYP2C9 *2, *3,

VKORC1*2 (G-1639A) alleles explained 49 % in dose

variation during long-term treatment (R2 = 0.49). The

addition of VKORC1 *3 (G3730A) allele into the formula,

increased the accuracy by 1 % (Table 6).

Discussion

Thus, the main purpose of this study was to find whether

VKORC1 (G3730A) and CYP4F2 (G1347A) genotypes

determine the variability in warfarin dose during induction

and continuing the use of warfarin for more than 3 months.

Thus, we also demonstrated that the impact of demo-

graphic, anthropometric, clinical parameters varies during

initiation of warfarin therapy after heart valve surgery and

during long-term treatment.

Higher doses of warfarin were prescribed during initia-

tion than during long-term treatment. So, during induction

the patients had higher INR (also they were better antico-

agulated) than during long-term treatment.

Table 5 Significant factors

affecting warfarin dosage at the

initiation stage of the treatment

a International normalized ratio

R2 for model 1st step R2

= 0.166 2nd step R2

= 0.325 3rd step R2

= 0.341

B p B p B p

Constant 9.150 \0.001 7.684 \0.001 6.127 0.002

Variable

Age -0.055 0.001 -0.063 \0.001 -0.065 \0.001

Body weight 0.021 0.1 0.022 0.06 0.022 0.06

INRa -0.422 0.04 -0.214 0.2 -0.203 0.2

Ambroxol -2.036 0.005 -1.575 0.01 -1.475 0.02

Amiodarone -1.137 0.005 -0.955 0.009 -1.008 0.005

CYP2C9 *2 -0.767 0.04 -0.827 0.02

CYP2C9 *3 allele variant -1.047 0.02 -1.227 0.01

VKORC1 *2 -1.527 \0.001 -1.558 \0.001

CYP4F2 A allele 1.776 0.01

Table 6 Significant factors

affecting warfarin dosage

during long-term treatment

a International normalized ratiob We write 1 for hypoactivity, 2

for normal activity, 3 for

hyperactivity

R2 for model 1st step R2

= 0.264 2nd step R2

= 0.491 3rd step R2

= 0.502

B p B p

Constant 7.121 \0.001 6.162 \0.001 5.801 \0.001

Variable

Age -0.055 \0.001 -0.055 \0.001 -0.051 \0.001

Body weight 0.032 \0.001 0.032 \0.001 0.033 \0.001

INRa -0.200 0.30 -0.416 0.01 -0.410 0.01

TSH levelb -0.593 0.08 -0.598 0.04 -0.627 0.03

Amiodarone -1.086 0.005 -1.035 0.01 -0.971 0.003

Benzodiazepines -1.157 0.02 -1.285 0.003 -1.268 0.002

Calcium channel blockers -1.667 0.002 -1.335 0.003 -1.368 0.002

CYP2C9 *2 -0.596 0.02 -0.562 0.03

CYP2C9 *3 allele variant -1.414 \0.001 -1.502 \0.001

VKORC1 *2 -1.268 \0.001 -0.991 \0.001

VKORC1 *3 0.414 0.02

V. Tatarunas et al.

123

Patient‘s age and body weight had stronger effect on

daily dosage of warfarin during long-term treatment, than

during initiation. It is well known, that patients’ age and

body weight are significant predictors of warfarin dose

[14].

The lower doses of warfarin (1 mg/day less) during

long-term treatment required these patients (14.8 %), who

had elevated the level of serum creatinine. Metabolites of

warfarin are excreted in urine. When kidney function is

impaired, higher levels of both warfarin and warfarin

metabolites are presented in the blood. Lower than normal

level of TSH having patients used more warfarin compared

to these, who had normal or higher TSH level. The function

of thyroid is anticipated by a signal transduced by TSH.

The activity of thyroid and the excretion of thyroxine

highly depend on TSH concentration in blood plasma.

Thyroxine is usually found in blood conjugated to albumin

and competes with warfarin to its binding site, so, it is often

observed, that patients, having higher FT4 concentrations

in blood, uses less warfarin [15, 16].

These patients, who concomitantly used such drugs as

ambroxol and amiodarone during initiation, required *2

and 1.5 mg per day less of warfarin, respectively, as

compared to non-users. Ketoprofen users required about

1 mg/day more than non-users. Amiodarone affects war-

farin dosage by blocking the activity of hepatic P450

cytochromes, especially CYP2C9, which is involved in the

metabolism of the main form of warfarin enantiomer—of

S-warfarin [17, 18]. Ambroxol is not only a potent se-

cretolytic agent, but it has a local anesthetic properties and

anti-inflammatory effect [19, 20]. As inflammation is one

of the causes of elevated activity of blood coagulation

system [3], it is possible, that anti-inflammatory activity of

ambroxol leads to a lower dosage of warfarin. Ketoprofen

blocks the activity of cyclooxygenase (COX), an enzyme,

which participate in the synthesis of inflammation factors

(such as PGE2). By blocking COX, inflammation and

blood coagulation are also suppressed [21]. Patients, who

did not receive ketoprofen, were treated with ketorolac or

diclophenac. These drugs are metabolized by CYP2C9. We

have not found any information on CYP2C9-dependent

metabolism of ketoprofen. It can be speculated that keto-

profen did not inhibit the activity of CYP2C9 as dicl-

ophenac or ketorolac.

During long-term treatment the users of such drugs as:

amiodarone, benzodiazepines, CCB’s and torasemide,

required less warfarin per day: 1.2, 1.4, 1.5 and 1 mg,

respectively, as compared to non-users. Long before, in

1972 Orme et al. [22] did not observe any interaction of

warfarin and benzodiazepines such as nitrazepam, diaze-

pam and chlordiazepoxide. In our case, patients used bro-

mazepam and lorazepam. In 1991 Domenici et al. [23]

found, that there is an allosteric interaction between

S-warfarin and benzodiazepines (S-lorazepam) binding

sites in human serum albumin. CCB’s are potent CYP3A4

inhibitors and may interact with R-warfarin metabolism. A

possible interaction mechanism of torasemide and warfarin

is still unclear [24].

More than 2/3 of the studied patients had CYP2C9 *1*1

genotype. A mean required a dose to obtain therapeutic

level of anticoagulation on warfarin dosage which was

6 mg/day for *1*1 carriers during induction and 5.3 mg/

day during long-term treatment. The carriers of variant

*1*2 and *2*2 genotypes required none the less of war-

farin than these, who had *1*1 genotype. A significant

reduction in daily warfarin dosage was observed in *3

allele carriers. They required about 2–3 mg less of warfarin

per day as compared to *1*1 (wild type) carriers. A

reduction in daily doses of warfarin were not so noticeable

for *2 carriers as compared to *3 allele carriers. We

obtained the same results for *3 allele carriers, as San-

derson et al. [25] was described. According by meta-

analysis done by Sanderson et al. [25] a reduction in

1.92 mg/day for *3 allele is observed, as the *3 allele

encodes an enzyme with the reduced metabolic activity.

The carriers of VKORC1 G1639G represented 39.7 % of

the studied patients. They were treated with the highest

doses of warfarin both during induction and during long-

term treatment. Variant allele carriers required less war-

farin than compared to G/G. The results were similar to

Gage et al. [6] who found, that A allele is associated with a

reduction of warfarin dosage by 28 %.

The carriers of VKORC1 A3730A represented 21.7 % of

studied sample. The presence of any G allele diminished

the daily warfarin dosage in the studied patients’ sample. In

the recently published work (2012) VKORC1 G3730A

genotype was associated with the requirement of higher

warfarin doses [5].

During initiation the daily doses of warfarin did not

differ in CYP4F2 G/A and G/G carriers, but about 1 mg/

day higher doses were prescribed to A/A genotype carriers.

The latter’s represented only 5.3 % of the patients. On the

contrary, homozygous A/A required about 1.5 mg/day less

of warfarin to maintain the therapeutic INR during long-

term treatment than compared to initiation stage. In 2008

Caldwell et al. [10] observed a difference of 1 mg in daily

warfarin dose in three independent white patients cohorts

stabilized on warfarin, but in 2012 Bejarano-Achache et al.

[12] was noted that, the genotype of CYP4F2 can have a

measurable effect during induction of warfarin therapy.

The effect of CYP4F2 V432 M polymorphism, namely

G1347A (rs2108622) on daily warfarin dosage was

explained in 2009 [11]. In vitro experiment demonstrated

that, vitamin K1 was metabolized to a single product by

human hepatic microsomal CYP4F2. Thus, the carriers of

M allele (1347A) had lower metabolism rate of vitamin K1

The effect of CYP2C9, VKORC1 and CYP4F2 polymorphism

123

and higher hepatic concentrations of active form of this

vitamin, resulting in higher dosage of warfarin to obtain a

required INR [11]. There is also another mechanism of

clinical importance which can play a significant role after

cardiac valve surgery: according to Du et al, the intensity

of inflammation depends on the metabolic activity of

CY4F2 enzyme [26].

Regression model for warfarin dose variation

During initiation, the variation in warfarin dose can be

explained by 32 % if such factors as patients’ age, body

weight, INR, concomitant medication use, CYP2C9*2, *3

and VKORC1 (G-1639A) polymorphism is detected. Fur-

thermore, the CYP4F2 G1347A genotype can in addition

explain 2 % of the dose variation. Other models repre-

senting the dosage of warfarin during initiation, includes

such factors as patients’ age, body weight, heart failure,

concomitant drugs, dietary supplements, CYP2C9 and

VKORC1 genotypes [27, 28]. In the recently published

article (2012) we have described a sample of only these

patients who were treated with ketoprofen after heart valve

surgery. The results showed that until a stable INR at the

target range of 2–3.5 is obtained during induction of war-

farin treatment after heart valve surgery, the dose of war-

farin may be explained by 43 % by such factors as patient

age, body weight, hepatic malfunction, use of concomitant

medication, VKORC1 *2 and CYP2C9*3 alleles [29].

On the contrary, during long-term treatment the allele *3

(VKORC1 G3730A) can explain about 1 % of warfarin

dose variation, but CYP4F2 genotype has no significant

impact on the dosage of warfarin. As it was described

earlier, CYP4F2 can be important during warfarin induc-

tion [12] as it controls the metabolism of vitamin K and can

have a significant effect if inflammation is taking place. We

have no explanation why VKORC1 *3 allele has a stronger

effect during long-term treatment than during induction.

Cini et al. [5] also found, that *3 allele had a measurable

effect during stable warfarin dosage. Further studies are

required to explain the action of these (CYP4F2 and

VKORC1) factors in inflammation and during long-term

treatment.

Conclusion

Our data confirmed that such factors as patient’s age, body

weight, concomitant medication use, CYP2C9 *2, *3 and

VKORC1 *2 alleles significantly affect the daily dosage of

warfarin as well as during initiation, as well as after

3 months of the treatment after heart valve surgery. The

novelty is that the carriers of CYP4F2 A1347A genotype

required higher daily warfarin doses during initiation of

warfarin therapy after heart valve surgery than comparing

to G/G and G/A carriers. During the longer periods of

warfarin use, the dosage of warfarin depended significantly

on VKORC1 *3 allele (G3730A polymorphism) and on the

thyroid stimulating hormone level in the blood plasma.

Acknowledgments These studies were funded by a Grant (No.

LIG-26/2010) from the Research Council of Lithuania.

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