The Influence Of Genetic Polymorphisms Biology Essay

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Warfarin is widely prescribed for the patients to prevent the thromboembolic events. It is used for various clinical conditions such as deep vein thrombosis, pulmonary embolism, atrial fibrillation, valvular heart diseases, coronary heart diseases and patients undergoing cardiac surgery for valvular replacements [1-5]. It is a narrow therapeutic index drugs and needs careful monitoring. To ensure the safety and effectiveness of oral anticoagulants, the dose must be adjusted accurately and frequently. The effectiveness and safety of warfarin therapy is critically dependent on monitoring the prothrombin time (PT) and interpreted as the International normalized ratio (INR) [6].

Bleeding is the main complication of oral anticoagulant therapy. Adverse events are common with warfarin, thus being a second leading cause of drug induced hospital admissions [7]. The fatal incidence of adverse drug reactions due to warfarin therapy was reported to be greater than 13.4% [8]. The intensity of anticoagulant effect is probably the most important risk factor for intracranial hemorrhage. The risk increased dramatically with an INR > 4.0 to 5.0 [9]. Another complication of warfarin therapy is therapeutic failure, an event that produces unintended thromboembolism due to suboptimal anticoagulation in patients.

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There is large inter-individual variability in warfarin dose requirement, this may be due to the influence of many factors, including age, sex, genetic variants, illness, and drug interactions. Furthermore, genetic polymorphism in the enzymes responsible for warfarin metabolism and its pharmacodynamic action affects dosage requirements. The genes mainly involved in the anticoagulant pathway are: cytochrome P450 2C9 (CYP2C9), vitamin K epoxide reductase complex 1(VKORC1), cytochrome P450 4F2 (CYP4F2) and gamma glutamyl carboxylase (GGCX).

Furaya et al (1995) [10], - first to report the influence of CYP2C9 polymorphism on warfarin dose requirement in vivo, CYP2C9*1/*2 genotype required 20% lower warfarin dose to maintain target INR (2-4), 90% patients receiving the lowest warfarin dose were CYP2C9*2 carriers. Followed by Furaya et al, many studies demonstrated that patients with CYP2C9 (CYP2C9*2 and CYP2C9*3) variant alleles leads to sensitivity to warfarin dose and are at increased risk of over anticoagulation and bleeding complications [11-14].

The genetic polymorphisms of VKORC1 are significant determinants of individual dose requirement. Several common variants of VKORC1 were reported to influence the warfarin dose requirement, among them the promotor region polymorphism (-1639 G>A), SNPs in the noncoding regions and SNP in the 3'UTR regions are most studied [15- 17]. The variant allele in VKORC1 were reported to exhibit a strong linkage disequilibrium (LD) (D'>0.9) [16]. Previous studies have demonstrated that the haplotypes of VKORC1 significantly influence the warfarin dose requirement [16].

A common variant in the CYP4F2 (rs2108622) was found to be associated with reduced hepatic CYP4F2 enzyme activity and higher levels of vitamin K (VK). Presence of this variant allele is associated with higher warfarin dose requirements [18]. Carriers of the CYP4F2 V433M allele have a reduced capacity to metabolize VK. Therefore, patients with the CYP4F2 variants are likely to have elevated hepatic levels of VK and thus are likely to require a higher warfarin dose to prompt the same anticoagulant response. The gamma- glutamyl carboxylase (GGCX) is responsible for carboxylation of clotting factors (glutamic acid containing glycoproteins) required to form the clot. The genetic polymorphism in the gene encoding GGCX leads to decreased warfarin dose requirement [19].

Recent studies have demonstrated the pharmacogenetic models using the genetic polymorphism of CYP2C9, VKORC1 and clinical factors also included in the models to facilitate the more accurate predictions of warfarin dose in various populations [20-23]. Few more studies have included the CYP4F2 variant in the models [24]. However, the developed models were more appropriate for the specified study populations. Very few studies have explained the genetic influence and warfarin dose requirement in Indian patients [25].

South Indians constitutes about 28.97% of the total population of India and resides in four states [Andhra Pradesh (6.99%), Tamil Nadu (5.96%), Karnataka (5.17%) and Kerala (2.75%)] and a union territory [Pondicherry (0.10%)]. (http://www.censusindia.gov.in/2011-prov-results/paper2-vol2/data_files/India2/Table_1_PR_Districts_TRU.pdf). This population shares a common ancestry (Dravidians), but the present day population differs from one another in terms of language, culture and dietary habits with limited admixture. David Reich et al., [26] found that the ancestral south Indians were distinct from the ancestral north Indians and east Indians. In our previous studies we have explained south Indians are significantly different than Caucasians, African Americans, Asians and other population in terms of genetic polymorphisms in pharmacogenetic studies [27-30].

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In our hospital warfarin is widely prescribed for patients to maintain anticoagulation levels for various conditions. The pharmacogenomics of warfarin was well studied in the world population. In our population, there were no much information regarding the association of warfarin and genetic polymorphisms. Hence, in the present study, we aimed to ascertain the influence of genetic variability of CYP2C9, VKORC1, CYP4F2 and GGCX genes including 11 SNPs on warfarin maintenance dose requirement in the south Indian patients and to develop pharmacogenetic algorithm to predict the warfarin dose based on the genetic and clinical factors.

Materials and Methods

Study subjects

The study was conducted on patients attending the outpatient clinics of department of cardiothoracic and vascular surgery and department of cardiology at Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER) Hospital, Puducherry. The patients belonged to South India and their nativity was assessed by family history of three generations living in four states (Tamil Nadu, Kerala, Karnataka and Andhra Pradesh) and a union territory Pondicherry. The study was approved by Institute Ethics Committee of JIPMER and the study was conducted according to declaration of Helsinki. All the study participants were explained about the study and written informed consent was obtained

All study participants were on anticoagulation treatment with warfarin for prevention of thromboembolism for various conditions (Table 1). The mean daily maintenance dose (mg/day) of warfarin was defined as "patients receiving the dose of warfarin for a period of at least 3 months with three or more consecutive INR measurements within target range (2 to 3.5) to prevent thromboembolism".

Dose modifications were made based on American College of Chest Physician (ACCP) guidelines (8th Edition) for warfarin therapy. The study participants belonged to the age group of 18-65 years and of either gender. Data on participants' age, height, weight, body mass index, medication history, INR values, and warfarin dose were obtained from patient case records. Patients who were on concomitant therapy with drugs potentially interacting with warfarin, patients with liver or renal dysfunction, pregnant and lactating women, smokers, and alcoholics were excluded from the study.

Genotyping of CYP2C9, VKORC1, CYP4F2 and GGCX

Five milliliters of venous blood were collected from the patients for estimation of prothrombin time and calculation of INR. Residual blood samples after estimation of INR were used for genotyping. DNA was extracted by phenol-chloroform extraction procedure. Genotyping for polymorphisms of CYP2C9, VKORC1, CYP4F2 and GGCX were done with Real-Time Thermo Cycler (7300 Applied Biosystems; Life Technologies Corporation, Carlsbad, CA, USA) using TaqMan SNP genotyping assays (Table 2). The PCR was carried out in triplicate in a 25-µL final volume that contained 12.5 µL of TaqMan universal PCR master mix (2x), 1.25 µL of 20Ã- working stock of TaqMan SNP genotyping assay, and 5.0 µL of genomic DNA diluted in DNAase free water and 6.25 µL of MilliQ water (Millipore Corporate Headquarters, Billerica, MA, USA). The thermo cycler conditions included one cycle at 95°C for 10 min to activate the AmpliTaq gold DNA polymerase followed by 45 cycles of denaturation at 92°C for 15 s and annealing/extension at 60°C for 1 min. The genotype and allele calls were analyzed using 7300 SDS software version 1.4.0.

Statistical analysis

GraphPad Instat® version 3.06 (San Diego, USA) and IBM® SPSS® Statistics version 19.0 (SPSS Inc., Chicago, IL, USA) were used for statistical analysis. The genotype frequencies were analyzed for Hardy-Weinberg equilibrium using Chi-square test. The mean daily maintenance doses were compared between the genotype groups using Kruskal Wallis test (Dunn's post hoc test) and Mann-Whitney U-test.

Pairwise linkage disequilibrium (LD) pattern and haplotype frequencies were estimated using HAPLOVIEW 4.1 (Daly Lab, Broad Institute, Cambridge, USA) [31]. All the SNPs with minor allele frequencies of 0.01% were excluded and minimum haplotype frequency was set as 1%. Haplotype blocks were defined by using solid spine rule incorporated by analysis in HAPLOVIEW software. Haplotypes were estimated by accelerated expectation-maximization (EM) algorithm in HAPLOVIEW. The confidence interval range for LD was set between 0.5 and 0.99. D' values from 0.8- 1.0 indicates strong LD between pair of SNPs. Whereas D' value<0.8 indicates moderate LD and D' value of <0.2 indicates no LD.

The association between the genotype and drug dose was evaluated using linear regression analysis. Stepwise multivariate regression analysis was used to ascertain the influence of the independent variables (clinical and genetic) on the dependent variable (logarithmic transferred daily maintenance dose). A p value less than 0.05 was considered statistically significant. All SNPs were included in the univariate and multivariate analysis, the homozygote wild type, heterozygote variant and the homozygote variant genotypes were coded as 0,1 and 2, respectively. Age, body weight, height, BMI were included as continues variables.

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Results

Demographic and clinical characteristics of the patients

A total of 257 patients were recruited for the study among them 240 data were included for the analysis, 17 patients data were excluded due to either lack of complete data and lose of samples when processing of DNA extraction and poor quality of the DNA. Among the 240 patients male and female were 36.7% and 63.3%, respectively. In approximately 74.2% of patients, the indication for warfarin treatment was rheumatic heart disease with mitral stenosis, mitral valve regurgitation and post atrial valve replacement. Dilated cardiomyopathy and atrial fibrillation were reported to be 4.6% and 3.8%, respectively. The demographic and clinical conditions of the patients were described in Table 1. All the patients were under maintenance warfarin therapy for at least three months with the INR range 2.0 to 3.5. Furosemide and phenoxymethyl penicillin were found to be widely prescribed as concomitant drugs with warfarin.

Genotype analysis

In the present study, the genotype frequencies of CYP2C9*1*1, CYP2C9*1*2, CYP2C9*1*3 and CYP2C9*2*3 were found to be 78.7%, 6.7%, 13.8% and 0.8%, respectively. The allele frequencies of CYP2C9*1, CYP2C9*2, and CYP2C9*3 were found to be 88.9%, 3.8% and 7.3%, respectively. The allele and genotype frequencies in the present study were similar to those reported for the South Indian population in our previous study. The genotype and allele frequencies of VKORC1, CYP4F2 and GGCX were described in Table 2. The genotype frequencies of all the variants were found to be in Hardy-Weinberg equilibrium.

Haplotypes of VKORC1

Eight major haplotypes were identified with minimum allele frequencies >1% among the 7 SNPs of VKORC1. The linkage disequilibrium analysis revealed that a very strong LD pattern (D'>0.8) were observed with the SNPs rs7294, rs2359612, rs8050894, rs9923231 and rs7196161. A moderate LD pattern (D'<0.8 to >0.5) observed with SNPs rs9934438 and rs2884737 (supplementary file Figure 1). Among the eight major haplotypes (supplementary file Table 1) the haplotype H1 (ACGCTGT) was more frequent (74.0%). The H1 haplotype constitute variant alleles of rs7294. The mean dose (5.46±1.96 mg/day) in the H1 group was significantly different from other haplotype groups. The reference haplotype H2 constitutes of all the wild type allele among the 7 SNPs (GCGCTGT) and the frequency was reported to be 9.0% with mean dose (5.83±1.44 mg/day) significantly higher than the other combinations. However, the mean dose of H2 haplotype group not significantly differed from the H1 haplotype group. The other haplotype groups constitute of variant alleles in the any of the 7 SNPs leads to significantly decreased daily dose of warfarin.

The difference in daily maintenance dose of warfarin in different genotype groups

The mean daily warfarin maintenance dose was found to be 4.71±2.15 (mean±SD) mg/day. Patients with the CYP2C9*1*2, CYP2C9*1*3 and CYP2C9*2*3 variant genotype required 50.9%, 43.1% and 62.2% lower daily maintenance dose of warfarin (2.78± 1.49 (SD) mg, 3.15±1.36 (SD) mg and 2.25±0.35 (SD) mg, respectively) than the normal CYP2C9*1*1 genotype group (5.18± 2.09 (SD) mg). The influence CYP2C9 genotypes on mean daily warfarin dose are illustrated in Figure 1.

The influence of VKORC1, CYP4F2 and GGCX genotypes on daily maintenance dose were given in Table 3. Among the VKORC1 variants studied the promoter region (rs9923231 G>A) variant and the intron variants (rs2884737, rs9934438, rs80850894 and rs235912) were found to be significantly reduced the daily required dose. Patients having one defective allele in VKORC1 rs9923231, rs2884737, rs9934438, rs80850894 and rs235912 required significantly lower daily maintenance dose of warfarin (47.97%, 32.94%, 48.41%, 36.73% and 33.33% mg/day, respectively) than normal genotype carriers. Patients having two defective alleles in rs9923231, rs9934438, rs80850894 and rs235912 required 85.57%, 88.96%, 78.43%, 80.62% mg/day, respectively lower daily maintenance dose of warfarin than normal genotype carriers.

There was no homozygous variant reported in rs2884737. The VKORC1 rs7196161 and the UTR 3' variant rs7294 carriers required significantly higher doses of warfarin than the normal genotype carriers. The variant allele in CYP4F2 (GA and AA) required significantly higher doses of warfarin (19.74% and 49.04%, respectively) than the normal genotype carriers. The variant allele in GGCX (CG) required significantly lower doses of warfarin (45.86%) than the normal genotype carriers.

Regression analyses

A univariate analyses were performed to analyses the influence of 19 individual factors on daily warfarin dose requirement (Table 4). We have identified a total of 17 factors associated with warfarin dose requirements, two factors (Vegetable intake and serum albumin) were not significantly influence the daily maintenance dose in our patient group. Among the 17 factors six patient related factors (age, sex, clinical condition, height, weight, BMI) and 11 genetic factors in the CYP2C9 (*2 and *3), VKORC1 (rs9923231, rs2884737, rs9934438, rs80850894, rs235912, rs7196161 and rs7294), CYP4F2 (rs2108622) and GGCX (rs11676382) were significantly influenced the daily warfarin maintenance dose.

The multivariate analysis was performed by adding the factors results from univariate analysis in order to select the variables that are included in the final model (Table 5). Among the 17 factors influenced in the univariate analyses only 11 factors were significantly associated together on daily maintenance dose. Among the 11 factors in the model the genetic variation of VKORC1 rs9923231 alone contributed up to 27.5% variation of required dose. The multivariate model analyses revealed that clinical and genetic factors together contribute to 62.1% (adjusted r2=0.602, p<0.0001) of variation in daily maintenance dose of warfarin. The genetic factors are the major predictors (46.6%) of warfarin dose in south Indian population. The stability of the multivariate model was confirmed by 1,000 bootstrap replications from the original data. The bootstrap validation was performed to find out the percent variance in warfarin dose requirement. There was no difference observed and the accuracy of the original estimate and the bootstrap estimate was found to be 100%. There was a significant correlation observed between the actual dose and the predicted dose calculated by using the multivariate model (Figure 2).

Discussion

The purpose of the present study was to develop a new dosing algorithm in the south Indian population that considers, in addition to clinical data and SNPs associated with warfarin sensitivity (CYP2C9*2, CYP2C9*3, VKORC1 (rs9923231, rs7196161, rs2884737, rs9934438, rs8050894, rs23596121 and rs7294), CYP4F2 (rs2108622) and GGCX (rs11676382) and resistance (unaccounted in most previous studies). In the present study the genotype and allele frequencies of CYP2C9 and VKORC1 were similar to our previous study reports. The effect of additive and dominant models on warfarin dose was studied in the VKORC1, CYP4F2 genotype groups. There were no homozygous variants in the VKORC1rs2884737 and GGCX rs11676382; hence the additive and dominant models were not compared in these genotypes. In other genotype groups we have observed significant differences (Table 3).

We also found that warfarin dose requirement decreased with increased age (2.7%). Weight is the significant demographic factor which shows 9.2% variability in warfarin dose. CYP2C9 genetic variants contributes up to 12.4% variability, VKORC1 genetic variants together contribute up to 32.4% variability, CYP4F2 and GGCX variants contribute up to 1.9% and 0.6%, respectively. The GGCX genetic variant was found to be rare in our population, however the influence was significant (univariate r2=0.019, p<0.05).

Many studies have explained that the single nucleotide polymorphism of VKORC1 in the pharmacogenetic model is predictive factor for warfarin dose requirement [32-36]. Our study showed that multiple SNPs can be used to predict the warfarin maintenance dose. The haplotypes of the VKORC1 showed that, among the 7 SNPs, rs7294 G>A was the more frequent and associated with higher warfarin dose (haplotype H1); the remaining wild type allele (haplotype H2) was associated with higher warfarin dose requirement. The haplotypes observed in the present study was similar to our previous study in Tamilian population [37]. Also, the previous study by Lal et al [38] explained that the haplotype TCGTCA (H7) was reported to be more common in Indians. In agreement with this study in the present study ACGCTGT haplotypes were reported to be associated with higher warfarin dose requirement and our patients required an intermediate warfarin dose. Several studies demonstrated that noncoding region SNPs in VKORC1 influenced warfarin sensitivity. Further study demonstrated that nine haplotypes were constructed from 10 polymorphisms in VKORC1 that showed association with warfarin dose requirement [16]. In that study, the haplotypes associated with the highest warfarin dose all carried the 1173 C allele. In line with this study we have observed that haplotypes with 1173 T allele required lower warfarin dose than the 1173 C allele carriers. Studies also showed that CYP2C9 and VKORC1 genetic polymorphisms significantly influence in warfarin dose requirement ≃ 5- 20% and ≃ 13-34%, respectively [39,40]. In the present study we have observed that CYP2C9 and VKORC1 contribute up to 12.4% and 32.4%, respectively. According to the previous study and our findings the effect of genetic polymorphisms of CYP2C9 was smaller than VKORC1 on warfarin maintenance dose. Many studies were conducted in different ethnic population and shows that the predictions of pharmacogenetic models as well as the predicting factors in the models were differed from one another (Table 6). Most of the clinical variables in the algorithms were similar; however there was a large inter-ethnic variations in the genes encountered for pharmacogenetic predictive models. The most commonly included loci in the algorithms were CYP2C9*2, CYP2C9*3 and VKORC1 -1639 G>A. Few studies were included the other loci such as CYP4F2, GGCX and EPHX1. [41, 42]

There was a large inter-ethnic variation observed in terms of distribution of variant alleles in each population. The Asian individuals completely lack of the carriers of CYP2C9*2 alleles and it was reported that more prevalent in Caucasians, and in south Indians it was reported to be 4%. The CYP2C9*3 was reported to be 5.8% in Caucasians, 5.3% in Chinese, 2.3% in Japanese and it was reported to be more in south Indian populations (8%). [29] Further, the allele frequency of VKORC1-1639A was reported to be 10.8% in African American, 67.1% in Asians, 38.2% in Caucasians and 12% in south Indian population [37]. Further the CYP4F2 and GGCX also reported to be significantly differed in the world population [43].

There has been raising evidence to depict that ethnicity is a limiting factor of warfarin maintenance dose. A study conducted in Malays, Chinese and Indians revealed that the Indian patients required significant higher doses of warfarin than Malays and Chinese patients [36]. It is well demonstrated that there is a significant difference in warfarin dose among different ethnic populations; Asian patients required a lower warfarin dose than Caucasians [36].

Hence, there are large genetic variations in the inter-ethnic populations the proposed pharmacogenetic models were relevant only to the specific population from which population it was gained. This was suggested that the proposal of new pharmacogenetic algorithm in south Indian population. Furthermore, based on the genetic variant information the Asians (Orientals) required lower warfarin maintenance dose, Caucasians and African Americans required higher warfarin dose. In the present study we have observed that south Indians required intermediate warfarin dose.

The pharmacogenetic algorithm was developed by the international warfarin pharmacogenetics consortium in large sample size (n=4043) and validated in 1009 subjects. The pharmacogenetic algorithm accurately identified the weekly warfarin dose to achieve the target INR than did the clinical algorithm and fixed dose approach [44]. Many studies were conducted to test the pharmacogenetic algorithm based warfarin dose determinations, however few algorithms were validated in their patient cohort [32-36].Large randomized clinical trials are underway to quantify how the combination of pharmacogenomics based dose initiation and refinement affects laboratory and clinical outcomes. Some of the multi-centered, randomized clinical trials were conducted to compare the clinical algorithms with pharmacogenetic algorithms [45, 46]. Two major prospective multicentre randomized clinical are currently evaluating whether pharmacogenetics-guided dosing improves patient outcomes. The U.S. trial, Clarification of Optimal Anticoagulation through Genetics (COAG) and the European trial, called Pharmacogenomics Approach to Coumarin Therapy (EU-PACT). The COAG trial will be conducted to in one half of the patient receiving the clinical based dosing, and other half receiving based on IWPC. The EU-PACT trial will compare the outcomes of dosing regimens in patients already know their genotype and those do not know, for the first three months of therapy, in patients taking any oral anticoagulant (ClinicalTrials.gov Identifiers, NCT00839657, NCT01119300, respectively).

A study by Pavani et al, [35] conducted in a south Indian population revealed that the pharmacogenetic algorithm predicted up to 44.9% of the dose requirements. They have reported that VKORC1 -1639 G>A, VKORC1*3, VKORC1*4, CYP2C9*3, male gender, CYP2C9*2, vitamin K intake, age, body mass index were the major predictive factors and CYP2C9*3, VKORC1-1639 G>A and VKORC1*3 polymorphisms were associated with warfarin sensitivity. However, in the present study we have reported that age, body weight and clinical conditions such as post mechanical heart valve replacement were the important clinical factors to predict warfarin dose. The genetic polymorphisms of CYP2C9 (CYP2C9*2 and CYP2C9*3), VKORC1 (rs9923231, rs7294, rs9934438 and rs2359612), CYP4F2 (rs2108622) and GGCX (rs11676382) were the important genetic factors to predict the warfarin dose in south Indian patients. The clinical and genetic factors together contributed to 62.1% variability of required warfarin dose in south Indian patients.

Recently, the United States Food and Drug Administration (US FDA) updated the label of warfarin twice: in 2007 advising physicians to consider the use of "genetic tests to improve their initial estimate" of the initial dosage, then in 2010 adding a new table with the range of expected therapeutic warfarin doses based on CYP2C9 and VKORC1 genotypes (http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/2007/ucm108967.htm). Furthermore many studies have explained that other than CYP2C9, VKORC1, CYP4F2 and GGCX genes, CYP2C18, MDR1, EPHX1, Factor II, Factor X, PROC, PROS and many genes in the warfarin metabolism and its action are alter the warfarin dose requirement [41,47,48].

The major limitation of the present study was conducted under strict exclusion criteria (patients with interacting drugs, patients with liver and renal dysfunction, alcoholics and smokers, and geriatric age groups). Hence, the study presented only the exact degree of association of genetic variability on warfarin dose requirement without consideration of impact of environmental factors such as smoking, alcoholic and concomitant drugs. However, the patients attending the anticoagulant clinic in our hospital were well educated regarding the oral anticoagulation therapy by specially trained pharmacologists. Further studies with addition of other genetic factors such as SNPs in the CYP2C18, MDR1 and EPHX1 genes with a large sample size may significantly contribute to improvement our dosing model.

In conclusion, through the present study the effects of CYP2C9, VKORC1, CYP2C9 and GGCX genetic polymorphisms was explained in south Indian patients receiving warfarin maintenance therapy. Further the pharmacogenetic algorithm was established will be useful for predicting the starting dose of warfarin in south Indian patients.