Abstract
Background and objective
Warfarin is a commonly used oral anticoagulant with a narrow therapeutic index and various genetic and clinical factors that influence interpatient variability in dose requirements. This study investigated the impact of genetic and nongenetic factors on warfarin dose requirements in Egyptians.
Methods
DNA was extracted from 207 patients taking warfarin for more than 2 months and genotyped for VKORC1 (3673 G> A), CYP2C9 *2*3*4*5*8, CYP4F2 (V33M; rs2108622), APOE (rs429358, rs7412), and CALU (rs339097) gene polymorphisms. Linear regression modeling was conducted to identify the genetic and nongenetic factors that independently influence warfarin dose requirements.
Results
VKORC1 3673 AA or GA genotype (P < 0.0001), one or two variant alleles of CYP2C9 gene (P= 0.0004), APOE ε2 haplotype (P = 0.01), and increasing age (P < 0.0001) were all associated with lower warfarin dose, whereas smoking (P = 0.025) and pulmonary embolism (P = 0.0059) showed association with higher warfarin doses. These factors explained 31% of the warfarin dose variability. This is the first independent confirmation of the association of the CALU rs339097 variant with higher warfarin dose requirement, although inclusion of this single nucleotide polymorphism in the multiple regression model failed to achieve significance (P = 0.066). CYP4F2 (V33M) polymorphism was not significant (P = 0.314), despite its high frequency in the studied population (42%).
Conclusion
The study shows that VKORC1, CYP2C9 polymorphisms, APOE ε2 variant, and several clinical/ demographic variables are important determinants of warfarin dose requirements in Egyptian patients. The percentage of variability explained by these factors is lower than in those of European ancestry, but similar to the variability explained in Asians and African ancestry.
Keywords: APOE, CALU, CYP2C9, CYP4F2, Egyptian, polymorphism, warfarin, VKORC1
Introduction
Warfarin is ranked among the most prescribed drugs worldwide [1], but its use presents numerous challenges in clinical practice, as it is associated with considerable morbidity because of its narrow therapeutic range and large interpatient variability in dose requirements [2,3]. Numerous studies have described the genetic and nongenetic factors that influence warfarin dose requirements in those of European, Asian, and African ancestry [3,4]. Genetic variability in VKORC1 and CYP2C9 has been consistently replicated to associate warfarin dose. Several studies in those of European ancestry have also suggested a role for CYP4F2, a recent report suggests a role for CALU in those of African ancestry, and APOE has been variably associated [5]. However, there are limited data on associations in Middle Eastern or Mediterranean populations.
The primary objective of this study was to determine the genetic and nongenetic factors associated with warfarin dose requirements in Egyptians.
Methods
Study population
The study was approved by the Research Ethics Committee at the Faculty of Medicine, Ain Shams University, Cairo, Egypt. A total of 207 Egyptian patients signed the written informed consent and participated in this study. Eligible patients were enrolled at four sites in Cairo, one hundred patients were enrolled from an Egyptian Cardiology Clinic, sixty-three patients were enrolled from Nasser Institute Hospital, twenty-nine patients from the Cardiology Clinic at Al Azhar University, and fifteen patients from Demerdash Hospital.
Patients were considered eligible if they were taking stable weekly doses of warfarin (Marevan; GlaxoSmith Kline, Cairo, Egypt) for three consecutive clinic visits, occurring over a minimum time period of 2 months. A stable weekly maintenance dose of warfarin means a dose that did not vary by more than 10% between clinic visits. The international normalized ratio (INR) at each of the three visits had to be in the patient’s specific goal INR range. As in earlier studies, one of the three INR readings was 0.2 units, which was above or below the goal INR range because of the inherent variability in the INR measurement [6]. Patients with liver cirrhosis, advanced malignancy, hospitalization within the earlier 4 weeks, and those who suffered from febrile/diarrheal illness within the past 2 weeks were excluded from the study.
Clinical data were collected and double-checked from different sources to get the most precise data for each case. A brief interview with each patient was conducted in which they were asked to document the following information: age, body weight, height, sex, smoking status, alcohol history, indication for warfarin use, weekly prescribed warfarin dose, earlier history of hemorrhage, past medical history, and concomitant medications taken during the past three clinic visits. Finally, a blood sample for DNA isolation and genotyping was obtained from each patient.
Genotyping procedure
Blood samples (5 ml) were taken from each patient for INR measurement and DNA extraction. Genomic DNA was extracted from samples of peripheral blood leukocytes using either a QIAamp DNA Blood Mini Kit (183 samples; QIAGEN, Cairo, Egypt) or automated QIAcube device (24 samples; QIAGEN, Cairo, Egypt) according to the manufacturer’s guidelines. CYP2C9 polymorphisms; CYP2C9*2 (Arg144Cys), CYP2C9*3 (Ile359Leu), CYP2C9*4 (Ile359Thr), CYP2C9*5 (Asp360Glu), VKORC1 3673G>A, and APOE (rs429358 and rs7412) genes were genotyped in by PCR followed by pyrosequencing based on a published assay from our laboratory [6–8]. CYP4F2 (Val433Met) was genotyped by TaqMan assay [9–11]. The genotyping of CYP2C9*8 (Arg150His) was performed by PCR-restriction fragment length polymorphism method, using AciI restriction endonuclease enzyme and with assay validation confirmed by direct sequencing and known CYP2C9*8 carrier samples used as positive controls [12–13]. The CALU (rs339097) single nucleotide polymorphism (SNP) was genotyped by PCR followed by pyrosequencing, in which the following PCR and sequencing primers were used: PCR forward: 5′-GGATTCTGAATCTGGCCAATAC-3′; reverse: 5′-biotin GGATTCTG AACAGGGACTCAGTTT-3′; and forward sequencing primer: 5′-TGAATCTGGCCAATACT-3′. The standard PCR reaction mixture used for the amplification of the target sequence consisted of 12.5 μl including 6.5 μl of ABI PCR mater mix with Taq DNA polymerase, 1 μl dimethylsulfoxide (Sigma-Aldrich, St Louis, Missouri, USA), 1 μl of each primer (Invitrogen, Carlsbad, California), 1.25μl of water for DNA, and 2 μl of genomic DNA.
Statistical analysis
Baseline demographics were analyzed using descriptive statistics. Numerical variables were represented as mean± standard deviation or median and interquartile range as appropriate. Categorical variables were presented as percentages. The mean weekly warfarin dose was calculated by taking the average of the warfarin dose of the patient, which was documented at each of the three consecutive clinic visits. Hardy–Weinberg equilibrium was tested by allele counting and χ2 analyses with one degree of freedom. Analysis of variance was used to compare the average warfarin dose between the genotype groups. Haplotype of APOE SNPs rs429358 and rs7412 was constructed using PHASE v2.1 software [14].
Mean weekly warfarin dose differences by genotype or haplotypes were evaluated by nonparametric methods. A stepwise linear regression model selection was used to assess the mean weekly warfarin dose in relation to genetic factors (VKORC1, CYP2C9, CYP4F2, APOE, and CALU genotypes), and nongenetic factors (sex, age, body surface area, use of aspirin, indication for warfarin, concomitant diseases, and smoking status). The genetic factors were coded as, (i) VKORC1 3673: AA genotype as 2, GAgenotype as 1, GG genotype (wild type) as 0, (ii) CYP2C9: *1/*1 genotype (wild type allele) as 0; heterozygous variant genotype (*1/*2, *1/*3, *1/*4, *1/*5, *1/*8) as 1, and homozygous variant genotype (*2/*2, *2/*3, *3/*3, *5/*5) as 2, (iii) CYP4F2 (Val433Met): CTand TT genotypes as 1, CC genotype (wild type) as 0, (iv) APOE (rs429358 and rs7412): haplotype TTwas coded as ε2, TC as ε3, and CC as ε4 alleles, respectively; and (v) CALU (rs339097): CT and CC genotype as 1, TT genotype as 0. Nongenetic factors that may contribute to warfarin dose requirements were also included in the model. These variables included age (decades), sex, indication for warfarin therapy, smoking status, and concurrent interacting medications. Square root transformation of the dose was applied to improve model fit and limit heteroscedascity. P value of less than 0.05 was considered significant. All statistical analyses were carried out with SAS (version 9.2; SAS Institute) and SPSS software (version 17.0 for windows; SPSS Inc., Chicago, Illinois, USA).
Results
A total of 207 Egyptian patients participated in this study; they are considered urbanites living in Cairo or other surrounding cities. Patients’ demographics, indication for warfarin, goal INR range, most common concomitant disease, and most common concurrent interacting medications taken are shown in Table 1.
Table 1.
Baseline demographics of warfarin-treated patients
| Demographic characteristics | All patients (n = 207) |
|---|---|
| Age (years) | 47.4 ± 14.7 |
| Sex | |
| Male | 93 (44.9%) |
| Female | 114 (55.1%) |
| Race | |
| Egyptian | 207 (100%) |
| Height (cm) | 166.7 ± 8 |
| Weight (kg) | 77.9 ± 15.7 |
| Indication for warfarina | |
| Atrial fibrillation | 2 (0.96%) |
| Mitral valve replacement | 107 (51.7%) |
| Deep vein thrombosis | 34 (16.4%) |
| Pulmonary embolism | 5 (2.4%) |
| Cerebrovascular accident | 22 (10.6%) |
| Aortic valve replacement | 26 (12.6%) |
| Cardiomyopathy | 5 (2.4%) |
| Others | 7 (3.36%) |
| Most common concomitant diseaseb | |
| Hypertension | 41 (19.8%) |
| Hyperlipidemia | 39 (18.8%) |
| Diabetes | 24 (11.6%) |
| Most concurrent interacting medicationsc | |
| Aspirin | 34 (16.4%) |
| Glimiperide | 9 (4.3%) |
| Goal INR range | |
| 1.5–2.0 | 9 (4.33%) |
| 2.0–3.0 | 197 (95.19%) |
| 2.5–3.5 | 1 (0.48%) |
INR, international normalized ratio.
Data are expressed as mean ± standard deviation or n (%).
Patients might have more than one indication for warfarin therapy.
Patients might have more than one concomitant disease.
Patients might have taken more than one concomitant interacting medication.
The study included 93 men and 114 women, with a mean age of 47.4±14.7 years. Indication for warfarin therapy varied, with mitral valve replacement as the most common indication for warfarin therapy (n=109, 52.7%). The mean warfarin dose was 36.8±17.9 mg/week, median was 35, and an interquartile range of 24.5–42 mg per week. The median of the mean INR for the whole study population was 2.25, with interquartile range of 2.1–2.4.
Complete genotyping data were available for 195 patients. All genotypes were in Hardy–Weinberg equilibrium (Table 2). DNA concentrations from the remaining 12 patients were too low to be genotyped. The minor allele frequencies (MAFs) of the SNPs study are contrasted between the Egyptian population studied here and population or published values for four other populations (Turkish, Asian, African–American, and Caucasian) (Table 2). These data suggest that MAFs among Egyptians cannot be assumed to be close to a specific continental population. For example, we observed variant alleles at CYP2C9 *4, *5, and *8, along with CALU rs339097, all of which are generally considered nonvariant in Caucasians, and observed primarily in those of African ancestry. In contrast, the MAF for CYP2C9 *2 and *3 was similar to Caucasians; CYP4F2 V433M was substantially higher than any other population reported to date, whereas APOE rs429358 was lower than typically observed in African–Americans or Caucasians. Thus, the MAFs for these various SNPs exhibit no consistent pattern in comparison with specific continental populations, even within a gene.
Table 2.
Comparison of CYP2C9 (*2,*3,*4,*5,*8), VKORC1 (3673G > A), APOE and CALU CYP4F2 minor allele frequencies in Egyptian, Turkish, Asian, African–American, and Caucasian populations
| Gene | Variant | Genotype | Frequency [n (%)] | Minor allele frequency |
Racial groups |
||||
|---|---|---|---|---|---|---|---|---|---|
| Minor allele | Egyptian (study population) | Turkisha | Asiana | African–Americana | Caucasiana | ||||
| CYP2C9 | *2 | CC | 151 (77.43%) | T | 0.117 | 0.106 | 0 | 0.02 | 0.143 |
| CT | 42 (21.54%) | ||||||||
| TT | 2 (1.03%) | ||||||||
| *3 | AA | 161 (82.56%) | C | 0.092 | 0.100 | 0.036 | 0.02 | 0.109 | |
| AC | 32 (16.41%) | ||||||||
| CC | 2 (1.03%) | ||||||||
| *4 | TT | 194 (99.49%) | C | 0.003 | 0.01 | 0 | 0 | 0 | |
| TC | 1 (0.51%) | ||||||||
| *5 | CC | 192 (98.46%) | G | 0.01 | 0 | 0 | 0.03 | 0 | |
| CG | 2 (1.03%) | ||||||||
| GG | 1 (0.51%) | ||||||||
| *8 | GG | 192 (98.46%) | A | 0.008 | 0.06 | 0 | |||
| GA | 3 (1.54%) | ||||||||
| VKORC1 | 3673 | GG | 50 (25.51%) | A | 0.462 | 0.50 | 0.87 | 0.12 | 0.43 |
| GA | 111 (56.63%) | ||||||||
| AA | 35 (17.86%) | ||||||||
| CYP4F2 | V433M | CC | 68 (35.42%) | T | 0.42 | 0.26 | 0.07 | 0.27 | |
| CT | 87 (45.31%) | ||||||||
| TT | 37 (19.27%) | ||||||||
| APOE | rs429358 | TT | 168 (86.67%) | C | 0.067 | 0.100 | 0.149 | ||
| CT | 26 (13.40%) | ||||||||
| rs7412 | CC | 169 (86.67%) | T | 0.074 | 0.040 | 0.087 | |||
| CT | 23 (11.79%) | ||||||||
| TT | 3 (1.54%) | ||||||||
| CALU | rs339097 | TT | 186 (95.38%) | C | 0.023 | 0.195 | 0 | ||
| CT | 9 (4.62%) | ||||||||
Information from Pharm GKB (http://www.pharmgkb.org/) and from NCBI dbSNP (http://www.ncbi.nlm.nih.gov/).
Dose requirements for each genotype group are shown in Table 3. For statistical comparison of warfarin dose by genotype, CYP2C9 polymorphisms, CYP2C9 genotypes were separated into three groups: wild type genotype (*1/*1), heterozygous variant genotype (*1/*2, *1/*3, *1/ *4, *1/*5, *1/*8), and homozygous variant genotype (*2/ *2, *2/*3, *3/*3, *5/*5). Among 122 wild-type homozygotes, 60 variant heterozygotes, and 13 variant homozygotes, the mean warfarin doses were 40.3±19.5, 31.7±14.8, and 32.0±14.1 mg per week, respectively (P=0.0028). Warfarin doses were also significantly different by VKORC1 genotype (P<0.0001), CALU (P= 0.04), and marginally significant for APOE ε2 (P=0.08), but not by CYP4F2 genotype (P=0.314; Table 3; Fig. 1).
Table 3.
Association of genetic polymorphism with warfarin dose requirements in Egyptians
| Gene | Variant | Genotype | Frequency (n = 207) | Mean ± SD warfarin dose (mg/week) | P valuea |
|---|---|---|---|---|---|
| CYP2C9 | *2*3*4*5*8 | *1/*1 | 122 (62.56%) | 40.3 ± 19.5 | 0.0028 |
| *1/*2 | 34 (17.44%) | 35.0 ± 16.9 | |||
| *1/*3 | 23 (11.79%) | 26.6 ± 10.4 | |||
| *1/*4 | 1 (0.51%) | 35 | |||
| *1/*5 | 2 (1.03%) | 28.0 ± 10 | |||
| *1/*8 | 3 (1.45%) | 39.7 ± 10.7 | |||
| *2/*2 | 2 (1.03%) | 29.8 ± 2.5 | |||
| *2/*3 | 8 (4.10%) | 32.4 ± 17.2 | |||
| *3/*3 | 2 (1.03%) | 33.3 ± 17.3 | |||
| *5/*5 | 1 (0.51%) | 31.5 | |||
| VKORC1 | 3673G > A | GG | 50 (25.51%) | 43.4 ± 21.6 | < 0.0001 |
| GA | 111 (56.63%) | 38.1 ± 16.4 | |||
| AA | 35 (17.86%) | 25.6 ± 12.3 | |||
| CYP4F2 | V433M | CC | 68 (35.42%) | 35.2 ± 16.1 | 0.31 |
| CT | 87 (45.31%) | 37.3 ± 18.7 | |||
| TT | 37 (19.27%) | 41.1 ± 20.9 | |||
| APOE | ε2/ε2 | 3 (1.54%) | 21.0 ± 3.5 | ε2 haplotype 0, 1, 2: P = 0.08 | |
| ε2/ε3 | 20 (10.26%) | 31.0 ± 15.1 | |||
| ε2/ε4 | 3 (1.54%) | 49.0 ± 18.2 | |||
| ε3/ε3 | 146 (74.87%) | 38.2 ± 17.9 | |||
| ε3/ε4 | 23 (11.79%) | 35.6 ± 22.0 | |||
| CALU | rs339097 | TT | 186 (95.38%) | 36.5 ± 17.9 | 0.04 |
| CT | 9 (4.62%) | 50.6 ± 21.3 |
SD, standard deviation.
These P values were generated using nonparametric methods (Kruskal–Wallis or Wilcoxon Rank-sum test as appropriate).
Fig. 1.
Effect of VKORC1, CYP2C9, CYP4F2, APOE ε2, and CALU genetic polymorphisms on warfarin dose requirements in Egyptians. Bars represent mean warfarin dose required. Error bars represent standard deviation. (P<0.05 is considered significant, test done by analysis of variance). APOE ε2 was coded as 0, 1, and 2 copies.
Results of the regression analysis are presented in Table 4. The R2 of the final regression model was 31.02%. The model shows that genetic and nongenetic factors were both predictors of warfarin dose requirement. Lower warfarin dose was associated with variants of VKORC1 3673, CYP2C9, and APOE ε2 and age, whereas smoking and pulmonary embolism, as indicated, were associated with higher warfarin dose. CALU (rs339097) was marginally significant, but did not meet the criteria to stay in the final model (P=0.066).
Table 4.
Linear regression stepwise modeling association between mean weekly warfarin dose (square root transformed) as a dependent variable and genetic and nongenetic factors as independent variables
| Predictor | Coefficient | Standard error | Partial R2 (%) | P value |
|---|---|---|---|---|
| Intercept | 8.06 | 0.32 | ||
| VKORC1 3673 genotype | −0.63 | 0.13 | 10.33 | < 0.0001 |
| Age (decades) | −0.30 | 0.06 | 8.11 | < 0.0001 |
| CYP2C9 | −0.41 | 0.14 | 5.17 | 0.0004 |
| Pulmonary embolism | 1.44 | 0.56 | 3.0 | 0.0059 |
| APOE ε2 | −0.60 | 0.22 | 2.53 | 0.01 |
| Smoking status | 0.58 | 0.26 | 1.88 | 0.025 |
| Model R2 | 31.02 | < 0.0001 |
Discussion
Populations in the Mediterranean represent some of the first populations to migrate out of Africa, which make them particularly interesting for genomics research [15]. Historical records show the Egyptian population is one that has undergone genetic admixture and racial mixing, which created a heavily mixed population of modern Egyptians including several ethnic groups such as Bedouins, Peasants, Nubians, Berbers, and urbanites [16]. The former ethnic groups each make up a relatively small percentage of the population and live along the coast, or in rural areas. Approximately 98% of the population lives within the Nile Valley and delta in towns or cities, the largest of which is Cairo. The population of the Nile valley and the delta forms a fairly homogeneous group whose dominant physical characteristics are the result of the admixture of the indigenous African population with those of Arab ancestry. Within urban areas (the northern delta towns especially), foreign invaders and immigrants, Persians, Romans, Greeks, Crusaders, Turks, and Circassians, long ago left behind a more heterogeneous mixture of physical types. Blond and red hair, blue eyes, and lighter complexions are more common there. Thus, this is an admixed population that has not been extensively investigated in genetic studies.
The aim of this study was to investigate the contribution of genetic and nongenetic factors on the variability of warfarin dose requirements in the admixed Egyptian population. The comparison of the MAFs of the SNPs studied showed no consistent patterns, with MAFs of SNPs ranging from being similar to Caucasians, to being similar to Africans, to being different from all earlier studied populations. These data highlight that polymorphism frequencies cannot be presumed to mirror those of European Caucasians or any other continental population. This is perhaps not surprising, given the presumed historical ancestral admixture of Egyptians. We are not aware of any population genetics studies that clearly define the ancestral makeup of Egyptians, and so the findings in this study, as it relates to MAFs, further supports recent recommendations of the importance of genomics research in the Mediterranean region [15].
Not surprisingly, we observed the highly replicated effects of VKORC1 and CYP2C9 on warfarin dose requirements. The contribution of CYP2C9 to variability in Egyptians was similar to that observed in Caucasians, while the contribution of VKORC1 to variable dose was much lower than in Caucasians, and more similar to what has been observed in African–Americans [8].
Studies of the CYP4F2 (V33M; rs2108622) polymorphism in whites, blacks, and Brazilians have shown an association with the warfarin dose requirement [9,17,18]. Despite the high frequency of CYP4F2 polymorphism in the Egyptian population (42%), we observed no significant association between the CYP4F2 (V33M; rs2108622) polymorphism and warfarin dose requirement (P= 0.314). However, a trend for dose differences by genotype was observed, with the direction being consistent with the literature.
We also studied the CALU SNP that was recently defined to lead to an approximately 11% higher warfarin dose for each variant allele in a primarily African–American population [5]. We are the first to confirm the association of the rs339097 variant with higher warfarin dose requirement, notably in a non-African–American cohort. We observed that variant allele carriers required 14.1 mg/ week more warfarin than TT homozygotes. Although inclusion of this SNP in our multiple regression model failed to achieve significance (P=0.066) this is likely an issue of power, as we only had nine variant carriers in our cohort. These data suggest, however, that CALU is likely to be an important contributor to high dose, and may be particularly relevant in non-Caucasian populations.
The literature on APOE is inconsistent. Some studies have shown the APOE ε4 allele to be associated with higher therapeutic warfarin dose [19,20]. In contrast, other studies have shown no association with warfarin dose and APOE genotype [8,19,21,22]. We observed that the APOE ε2 variants were significantly associated with lower warfarin dose requirements in the linear regression model (P= 0.01), although of borderline significance when considered alone.
This study also assessed the contribution of genetic and nongenetic factors to the interindividual variability of warfarin dose requirements. In the Egyptian population, 31% of variability in warfarin dose was explained by a combination of genetic and nongenetic factors. This is much lower than observed in most studies of Caucasians, although similar to the amount of variability explained by such factors in African–Americans and Asians [6,23,24]. For example, in the 5700 patient cohort that comprised the International Warfarin Pharmacogenetics Consortium, the model developed by the International Warfarin Pharmacogenetics Consortium explained 26% of the variability in African–Americans/blacks, and 33% of the variability in Asians [23]. In this study, VKORC1 3673G>A polymorphisms explained 10% in the warfarin dose variability, also much less than observed in most studies of Caucasians, but similar to the African–Americans [23]. CYP2C9 polymorphism explained 5% of the dose variability, which is at the lower end of the range of variability explained in many studies in Caucasians [6,24]. This shows that the inter-individual variability in warfarin dose requirements in the Egyptian population is due, at least partially, to additional genetic and nongenetic factors that need further investigation. This study population was generally younger, and had more patients with aortic valve replacement than those in other warfarin pharmacogenetic studies. This may have influenced the amount of variability in warfarin dose we could explain. In addition, the average dose in the five patients with the pulmonary embolism diagnosis was 70mg per week, although their INRs were not unusually high, averaging approximately 2.5. It is unclear why they would have required higher doses than the rest of the population and so significance of pulmonary embolism in the model may represent a chance finding. Finally, it was a surprise that a measure of body size (BSA in this case) was not a significant predictor of dose. We also modeled height and weight, with and without smoking, but no measures of body size were significant. It is possible that this is because of the minimal variation in height, which varied in the population by less than 4%.
In conclusion, this is the first report detecting the genetic associations of VKORC1, CYP2C9, CYP4F2, APOE, and CALU polymorphisms with warfarin dose requirements in Egyptian population. This study shows that genetic polymorphisms in VKORC1, CYP2C9, APOE, along with nongenetic factors are determinants of warfarin dose requirements. These factors explain less variability than has been shown in Caucasians, suggesting other important determinants of response variability remain to be determined.
Acknowledgments
This work was partially supported by a grant from Misr International University, Cairo, Egypt and NIH grant U01 GM074492. The authors thank Shimaa Mohamed at Clinilab, Cairo, Egypt, and Lynda Stauffer, Nicholas Carris and Brian Gawronski at the University of Florida, Center for Pharmacogenomics, Gainesville, Florida, for their laboratory assistance.
Footnotes
Conflict of interest: the authors declared no conflict of interest.
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